7 MISTAKES WRITERS ALMOST ALWAYS MAKE WHEN SELF-EDITING:

I’m still running and started knowing more stuff in editing. It took me a bit more time to re-share this post. I just keep on searching a bit deeper and a bit beyond on the odd and even stuff on editing. I got it from Pinterest. Still looking. This post will gonna help you and me. Like you and me as writers, we all edit after our writings. But being a self-editor, you and I need to do a lot groundworks.

I’m feeling good. These 7 mistakes will makes us a bad self-editor. Still, miles to go. Just be ready. Let’s work to be a better self-editor.

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With respect.

How to Get an ISBN for Your Book, Plus What You Should Do With It:

You are decided to write a book. Alright, your book is ready. Along with, it’s time to know a bit more on ISBN too. I wanna say it one more time, what is said yesterday. If you are searching something, fortunately, and unfortunately, rest other will fall. I’m really excited to read and re-share it.

This is the time to start research on ISBN procedures. May or may not we don’t know some of the stuff. Let’s look into it.

I’m gonna paste the source link down below. Please go further.

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ABOUT THE AUTHOR: LEAH CAMPBELL.

Leah Campbell has worked as a full-time freelance writer and developmental editor since 2013. A single mother by choice after a serendipitous series of events led to the adoption of her daughter, Leah is also author of the book Single Infertile Female.

Website | @LeahWritesStuff

When you set out to write and figure out how to self-publish a book, you probably had no idea how much would be involved in the process.

Sure, you knew it would be a lot of work. But now that you’re nearing the finish line, you realize how many extra steps you’ve had to take that you never before realized would be required.

We’re not just talking about book editing, revising and how to format a book. We’re also talking about choosing a self-publishing platform, marketing, and yes…getting an ISBN.

What is an ISBN?

Every book that ever makes it to print and becomes available for public sale, whether through traditional or self-publishing, requires an International Standard Book Number (ISBN).

These are unique 13-digit numbers (previously 10 digits, prior to December 2006) that help identify your book to libraries and book sellers, both online and on the street. The ISBN system is internationally used and recognized and the numbers within the ISBN represent five key elements:

  • A standard prefix
  • The country, geographical region, or language the book was published within
  • The publisher or imprint responsible for the book
  • The edition or format of the book
  • A single digit used to mathematically validate the rest of the number

What isn’t an ISBN?

An ISBN does not represent your copyright to the material. It doesn’t provide any legal protection to your creative work at all. It is purely an number meant to help identify your book to distributors, libraries, and booksellers around the world.

Why do you need an ISBN?

If you want your book to be sold and read anywhere beyond your own garage, you need an ISBN.

Without one, those already mentioned distributors, libraries and retailers won’t consider it a real book, and you will never have the opportunity to market your words to a larger audience.

How many ISBNs will you need?

Different formats require different ISBNs, even for the same book title. So if you are publishing a hard cover, a soft cover, an audiobook, and an e-book version, your book would require four ISBNs.

Additionally, if you make substantial changes to your book after publication so that the updated version would be considered a new edition, if you change the title or subtitle, or if you publish a version in larger print, you will also need a new ISBN for that. And if your book is published in multiple languages, each language version will need its own ISBN.

As you can see, a single book title can require quite a few ISBNs if you are aiming for multiple versions of that title. But for most self-publishers, an e-book and paperback ISBN will suffice.

Using a free ISBN

Once your book is completed, and you’ve selected a self-publishing platform, your first step should be to check to see if your self-publishing platform will provide a free ISBN as part of the publishing process. Some do, some don’t.

And in some cases, you may be able to receive a free ISBN for some versions of your book, but will need to purchase the ISBN for others (for instance, you may be able to get a free ISBN for your ebook, but have to purchase one for your paperback).

You might want to consider whether you will ever want to publish your book through a different platform. If that is a possibility, purchasing an ISBN may be a better option, as those provided for free through publishing platforms are generally only good through that platform.

If you want to be able to carry your ISBN with your book wherever it is published, it might be worthwhile to purchase one. Even if you could otherwise get it for free through your publishing platform.

How to purchase your ISBN

The good news is, obtaining an ISBN for your book is a relatively simple process.

  • If you are located in the United States, you will want to purchase yours through Bowker.
  • If you decide to purchase your own ISBN, Canadian residents can obtain theirs for free through ISBN Canada.
  • And those living in the UK, Ireland or British Overseas Territories can purchase their ISBNs through the Nielsen ISBN Store.
  • If you are located anywhere else, the International ISBN Agency can help you locate which agency you should be purchasing through. There are over 150 ISBN agencies in 200 countries, so rest assured there is one available to you.

How much does an ISBN cost?

The current cost of an ISBN through Bowker is $125 for a single ISBN number. However, Bowker also offers packages for those who see themselves doing more self-publishing in the future, or authors who are planning on publishing their book in various formats. You can purchase 10 ISBNS for $295. There are also options for purchasing 100 or 1,000 ISBNs at a time, but these are generally best suited for small publishers intent on publishing quite a few books over the next several years.

If you do purchase a package with multiple ISBNs, you do not have to assign them right way. You can save your additional ISBNs until your next book is ready for publication. Your ISBN numbers will never go bad or expire.

What to do with your ISBN once you have it

Once you have your ISBN, you should register it through Bowkerlink (or look for the registration site affiliated with your national ISBN agency). From there, you simply need to place your ISBN on your copyright page and provide it to your self-publishing platforms. You will also want to publish it on your back cover, above the barcode.

That’s it!

Your book is ready to be distributed to libraries and retailers. Or at least, it will be once you complete the publishing process!

 

SOURCE: https://thewritelife.com/how-to-get-an-isbn/

 

With respect.

 

33 UNUSUAL TIPS TO BEING A BETTER WRITER:

I felt this is an important moment to share this particular pic. This is one of the thought-provoking and beautiful post. If I miss this, I still no idea. When am I gonna share?

Quite honestly, I have a bit lot to share. Along with, I would love to share my thoughts too. So, I need to do simultaneously. Because of the editing posts, I wanna go farther. Let’s see. I need to challenge myself. I personally as a start-up writer, I need a vision for start-up editor too.

I got it. When I was researching on editing. Feeling a bit lucky and deserved.

I would say, I got a universal law of attraction. When you started searching something, certain stuff will fall. Actually, you don’t even know, what’s going on.

Feeling quite happy.

Finally, these 33 tips sound massive. Well finally, there is a lot to learn from 33.

Let’s jump into it.

33-unusual-writing-editing-tips

 

With respect.

 

5 PICS TELLS YOU HOW TO EDIT.

I’m quite happy. I am still looking further to know more about editing. I read a quote on editing when I started reading a bit more.

The secret to editing is simple:

“You need to become its reader instead of its writer” – ZADIE SMITH.

Even more, you must cut the irrelevant words. I see, as an editor, your duty is to form proper grammatical sentences. There is a possibility that you have to read 2 more times, the book you are editing.

Here are the 5.

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With respect.

 

 

WHAT IT TAKES TO BECOME AN EDITOR?

I should write more to edit. I should edit more from my writing. Bit crazy?

Alright.

But I should not edit someone’s blog or writings without their permissions. Rather, I would edit mine.

Why am I saying it?

I must understand and realize there is much more to edit from my own writings too.

Even for this post, I need to edit a lot more. I have to say, my progress is going like a marathon. More precisely, this it has no kilometres. As I say, it’s a life-long journey.

Let’s go:

  • If you wanna be an editor, you must have written a lot.

Additionally, you should have done a self-editing.

  • Well, grammar.
  • You should now lot more vocabularies.

Oh, readers please don’t mistake me. I am not contradicting here, if you hold an undergraduate or postgraduate degree in literature, definitely, it will gonna be great.

But I personally wasn’t from a literature background. Quite honestly, I have no idea of writing, when I was 15 years old. I’m writing diaries. I was absolutely crazy and ridiculous. So, my gut says, write every day, even you have a bad writing skills.

Then finally, I decided to take IELTS and TOEFL courses. I started preparing IELTS. I went to book stores and purchased relevant materials. Preparing. I wasn’t too good at English. I’m average. That doesn’t makes me upset. But I will take whatever, that needs to be done. Along with it, I started a bit deeper on APA and MLA styles guides.

Let’s pull back our attention towards the bulletin points.

  • You must have taken editing courses.
  • You must read fast and figure it out.
  • You must learn to convey politely to the writer that he/she made a mistake.
  • Please don’t mess with the writers. Because, they believe, as far they done very good editing on their book. They believe more, the rest would be taken by the editor.
  • Go-ahead with all the available research.
  • There is nothing wrong with admitting right or wrong.
  • Fortunately or unfortunately, you might not be perfect. Please take a challenge a try to perfect.
  • Don’t ever forget to nurture yourself.
  • Keep learning from whatever you are editing. There is something you can learn from something.

 

With respect.

 

MY 5 VALUABLE EDITING PICS:

I took a bit more serious about editing. I feel like, I would love to learn and be a good at it too.

I feel feverish, the butterflies in my stomach and a burning sensation towards editing. I’m crazy to do more on the editing part. I started thinking, how editing is such an important is for a writer. Because, I would debate, if a writer writes something, simultaneously, editing has to happen too. The writer has to do.

I would say to myself and the readers too. Please write and edit as far as you can.

Why am I saying?

When you wrote something and if you start editing. You feel the draft seems good. So, it doesn’t matter, after your book been written and goes to the editor. Those situations will gonna happen. That’s okay. Finally, that’s gonna be fine.

But. We as a writer could do it sincerely.

Oh, ladies and gentleman. Please don’t feel odd or awkward.

Why am I stretching the editing part?

Our drafts gonna be “GOOD”.

Here are the five editing pics. I would love to re-share it. Please have a look. Let me know if any suggestions in the comments below.

Constructive criticism accepted.

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With respect.

 

 

VALUABLE POEM: The Waste Land. By T. S. Eliot.

                   FOR EZRA POUND
IL MIGLIOR FABBRO

              I. The Burial of the Dead
  April is the cruellest month, breeding
Lilacs out of the dead land, mixing
Memory and desire, stirring
Dull roots with spring rain.
Winter kept us warm, covering
Earth in forgetful snow, feeding
A little life with dried tubers.
Summer surprised us, coming over the Starnbergersee
With a shower of rain; we stopped in the colonnade,
And went on in sunlight, into the Hofgarten,
And drank coffee, and talked for an hour.
Bin gar keine Russin, stamm’ aus Litauen, echt deutsch.
And when we were children, staying at the arch-duke’s,
My cousin’s, he took me out on a sled,
And I was frightened. He said, Marie,
Marie, hold on tight. And down we went.
In the mountains, there you feel free.
I read, much of the night, and go south in the winter.
  What are the roots that clutch, what branches grow
Out of this stony rubbish? Son of man,
You cannot say, or guess, for you know only
A heap of broken images, where the sun beats,
And the dead tree gives no shelter, the cricket no relief,
And the dry stone no sound of water. Only
There is shadow under this red rock,
(Come in under the shadow of this red rock),
And I will show you something different from either
Your shadow at morning striding behind you
Or your shadow at evening rising to meet you;
I will show you fear in a handful of dust.
                      Frisch weht der Wind
                      Der Heimat zu
                      Mein Irisch Kind,
                      Wo weilest du?
“You gave me hyacinths first a year ago;
“They called me the hyacinth girl.”
—Yet when we came back, late, from the Hyacinth garden,
Your arms full, and your hair wet, I could not
Speak, and my eyes failed, I was neither
Living nor dead, and I knew nothing,
Looking into the heart of light, the silence.
Oed’ und leer das Meer.
  Madame Sosostris, famous clairvoyante,
Had a bad cold, nevertheless
Is known to be the wisest woman in Europe,
With a wicked pack of cards. Here, said she,
Is your card, the drowned Phoenician Sailor,
(Those are pearls that were his eyes. Look!)
Here is Belladonna, the Lady of the Rocks,
The lady of situations.
Here is the man with three staves, and here the Wheel,
And here is the one-eyed merchant, and this card,
Which is blank, is something he carries on his back,
Which I am forbidden to see. I do not find
The Hanged Man. Fear death by water.
I see crowds of people, walking round in a ring.
Thank you. If you see dear Mrs. Equitone,
Tell her I bring the horoscope myself:
One must be so careful these days.
  Unreal City,
Under the brown fog of a winter dawn,
A crowd flowed over London Bridge, so many,
I had not thought death had undone so many.
Sighs, short and infrequent, were exhaled,
And each man fixed his eyes before his feet.
Flowed up the hill and down King William Street,
To where Saint Mary Woolnoth kept the hours
With a dead sound on the final stroke of nine.
There I saw one I knew, and stopped him, crying: “Stetson!
“You who were with me in the ships at Mylae!
“That corpse you planted last year in your garden,
“Has it begun to sprout? Will it bloom this year?
“Or has the sudden frost disturbed its bed?
“Oh keep the Dog far hence, that’s friend to men,
“Or with his nails he’ll dig it up again!
“You! hypocrite lecteur!—mon semblable,—mon frère!”
              II. A Game of Chess
The Chair she sat in, like a burnished throne,
Glowed on the marble, where the glass
Held up by standards wrought with fruited vines
From which a golden Cupidon peeped out
(Another hid his eyes behind his wing)
Doubled the flames of sevenbranched candelabra
Reflecting light upon the table as
The glitter of her jewels rose to meet it,
From satin cases poured in rich profusion;
In vials of ivory and coloured glass
Unstoppered, lurked her strange synthetic perfumes,
Unguent, powdered, or liquid—troubled, confused
And drowned the sense in odours; stirred by the air
That freshened from the window, these ascended
In fattening the prolonged candle-flames,
Flung their smoke into the laquearia,
Stirring the pattern on the coffered ceiling.
Huge sea-wood fed with copper
Burned green and orange, framed by the coloured stone,
In which sad light a carvéd dolphin swam.
Above the antique mantel was displayed
As though a window gave upon the sylvan scene
The change of Philomel, by the barbarous king
So rudely forced; yet there the nightingale
Filled all the desert with inviolable voice
And still she cried, and still the world pursues,
“Jug Jug” to dirty ears.
And other withered stumps of time
Were told upon the walls; staring forms
Leaned out, leaning, hushing the room enclosed.
Footsteps shuffled on the stair.
Under the firelight, under the brush, her hair
Spread out in fiery points
Glowed into words, then would be savagely still.
  “My nerves are bad tonight. Yes, bad. Stay with me.
“Speak to me. Why do you never speak. Speak.
  “What are you thinking of? What thinking? What?
“I never know what you are thinking. Think.”
  I think we are in rats’ alley
Where the dead men lost their bones.
  “What is that noise?”
                          The wind under the door.
“What is that noise now? What is the wind doing?”
                           Nothing again nothing.
                                                        “Do
“You know nothing? Do you see nothing? Do you remember
“Nothing?”
       I remember
Those are pearls that were his eyes.
“Are you alive, or not? Is there nothing in your head?”
                                                                           But
O O O O that Shakespeherian Rag—
It’s so elegant
So intelligent
“What shall I do now? What shall I do?”
“I shall rush out as I am, and walk the street
“With my hair down, so. What shall we do tomorrow?
“What shall we ever do?”
                                               The hot water at ten.
And if it rains, a closed car at four.
And we shall play a game of chess,
Pressing lidless eyes and waiting for a knock upon the door.
  When Lil’s husband got demobbed, I said—
I didn’t mince my words, I said to her myself,
HURRY UP PLEASE ITS TIME
Now Albert’s coming back, make yourself a bit smart.
He’ll want to know what you done with that money he gave you
To get yourself some teeth. He did, I was there.
You have them all out, Lil, and get a nice set,
He said, I swear, I can’t bear to look at you.
And no more can’t I, I said, and think of poor Albert,
He’s been in the army four years, he wants a good time,
And if you don’t give it him, there’s others will, I said.
Oh is there, she said. Something o’ that, I said.
Then I’ll know who to thank, she said, and give me a straight look.
HURRY UP PLEASE ITS TIME
If you don’t like it you can get on with it, I said.
Others can pick and choose if you can’t.
But if Albert makes off, it won’t be for lack of telling.
You ought to be ashamed, I said, to look so antique.
(And her only thirty-one.)
I can’t help it, she said, pulling a long face,
It’s them pills I took, to bring it off, she said.
(She’s had five already, and nearly died of young George.)
The chemist said it would be all right, but I’ve never been the same.
You are a proper fool, I said.
Well, if Albert won’t leave you alone, there it is, I said,
What you get married for if you don’t want children?
HURRY UP PLEASE ITS TIME
Well, that Sunday Albert was home, they had a hot gammon,
And they asked me in to dinner, to get the beauty of it hot—
HURRY UP PLEASE ITS TIME
HURRY UP PLEASE ITS TIME
Goonight Bill. Goonight Lou. Goonight May. Goonight.
Ta ta. Goonight. Goonight.
Good night, ladies, good night, sweet ladies, good night, good night.
              III. The Fire Sermon
  The river’s tent is broken: the last fingers of leaf
Clutch and sink into the wet bank. The wind
Crosses the brown land, unheard. The nymphs are departed.
Sweet Thames, run softly, till I end my song.
The river bears no empty bottles, sandwich papers,
Silk handkerchiefs, cardboard boxes, cigarette ends
Or other testimony of summer nights. The nymphs are departed.
And their friends, the loitering heirs of city directors;
Departed, have left no addresses.
By the waters of Leman I sat down and wept . . .
Sweet Thames, run softly till I end my song,
Sweet Thames, run softly, for I speak not loud or long.
But at my back in a cold blast I hear
The rattle of the bones, and chuckle spread from ear to ear.
A rat crept softly through the vegetation
Dragging its slimy belly on the bank
While I was fishing in the dull canal
On a winter evening round behind the gashouse
Musing upon the king my brother’s wreck
And on the king my father’s death before him.
White bodies naked on the low damp ground
And bones cast in a little low dry garret,
Rattled by the rat’s foot only, year to year.
But at my back from time to time I hear
The sound of horns and motors, which shall bring
Sweeney to Mrs. Porter in the spring.
O the moon shone bright on Mrs. Porter
And on her daughter
They wash their feet in soda water
Et O ces voix d’enfants, chantant dans la coupole!
Twit twit twit
Jug jug jug jug jug jug
So rudely forc’d.
Tereu
Unreal City
Under the brown fog of a winter noon
Mr. Eugenides, the Smyrna merchant
Unshaven, with a pocket full of currants
C.i.f. London: documents at sight,
Asked me in demotic French
To luncheon at the Cannon Street Hotel
Followed by a weekend at the Metropole.
At the violet hour, when the eyes and back
Turn upward from the desk, when the human engine waits
Like a taxi throbbing waiting,
I Tiresias, though blind, throbbing between two lives,
Old man with wrinkled female breasts, can see
At the violet hour, the evening hour that strives
Homeward, and brings the sailor home from sea,
The typist home at teatime, clears her breakfast, lights
Her stove, and lays out food in tins.
Out of the window perilously spread
Her drying combinations touched by the sun’s last rays,
On the divan are piled (at night her bed)
Stockings, slippers, camisoles, and stays.
I Tiresias, old man with wrinkled dugs
Perceived the scene, and foretold the rest—
I too awaited the expected guest.
He, the young man carbuncular, arrives,
A small house agent’s clerk, with one bold stare,
One of the low on whom assurance sits
As a silk hat on a Bradford millionaire.
The time is now propitious, as he guesses,
The meal is ended, she is bored and tired,
Endeavours to engage her in caresses
Which still are unreproved, if undesired.
Flushed and decided, he assaults at once;
Exploring hands encounter no defence;
His vanity requires no response,
And makes a welcome of indifference.
(And I Tiresias have foresuffered all
Enacted on this same divan or bed;
I who have sat by Thebes below the wall
And walked among the lowest of the dead.)
Bestows one final patronising kiss,
And gropes his way, finding the stairs unlit . . .
She turns and looks a moment in the glass,
Hardly aware of her departed lover;
Her brain allows one half-formed thought to pass:
“Well now that’s done: and I’m glad it’s over.”
When lovely woman stoops to folly and
Paces about her room again, alone,
She smoothes her hair with automatic hand,
And puts a record on the gramophone.
“This music crept by me upon the waters”
And along the Strand, up Queen Victoria Street.
O City city, I can sometimes hear
Beside a public bar in Lower Thames Street,
The pleasant whining of a mandoline
And a clatter and a chatter from within
Where fishmen lounge at noon: where the walls
Of Magnus Martyr hold
Inexplicable splendour of Ionian white and gold.
               The river sweats
               Oil and tar
               The barges drift
               With the turning tide
               Red sails
               Wide
               To leeward, swing on the heavy spar.
               The barges wash
               Drifting logs
               Down Greenwich reach
               Past the Isle of Dogs.
                                 Weialala leia
                                 Wallala leialala
               Elizabeth and Leicester
               Beating oars
               The stern was formed
               A gilded shell
               Red and gold
               The brisk swell
               Rippled both shores
               Southwest wind
               Carried down stream
               The peal of bells
               White towers
                                Weialala leia
                                Wallala leialala
“Trams and dusty trees.
Highbury bore me. Richmond and Kew
Undid me. By Richmond I raised my knees
Supine on the floor of a narrow canoe.”
“My feet are at Moorgate, and my heart
Under my feet. After the event
He wept. He promised a ‘new start.’
I made no comment. What should I resent?”
“On Margate Sands.
I can connect
Nothing with nothing.
The broken fingernails of dirty hands.
My people humble people who expect
Nothing.”
                       la la
To Carthage then I came
Burning burning burning burning
O Lord Thou pluckest me out
O Lord Thou pluckest
burning
              IV. Death by Water
Phlebas the Phoenician, a fortnight dead,
Forgot the cry of gulls, and the deep sea swell
And the profit and loss.
                                   A current under sea
Picked his bones in whispers. As he rose and fell
He passed the stages of his age and youth
Entering the whirlpool.
                                   Gentile or Jew
O you who turn the wheel and look to windward,
Consider Phlebas, who was once handsome and tall as you.
              V. What the Thunder Said
  After the torchlight red on sweaty faces
After the frosty silence in the gardens
After the agony in stony places
The shouting and the crying
Prison and palace and reverberation
Of thunder of spring over distant mountains
He who was living is now dead
We who were living are now dying
With a little patience
Here is no water but only rock
Rock and no water and the sandy road
The road winding above among the mountains
Which are mountains of rock without water
If there were water we should stop and drink
Amongst the rock one cannot stop or think
Sweat is dry and feet are in the sand
If there were only water amongst the rock
Dead mountain mouth of carious teeth that cannot spit
Here one can neither stand nor lie nor sit
There is not even silence in the mountains
But dry sterile thunder without rain
There is not even solitude in the mountains
But red sullen faces sneer and snarl
From doors of mudcracked houses
                                      If there were water
   And no rock
   If there were rock
   And also water
   And water
   A spring
   A pool among the rock
   If there were the sound of water only
   Not the cicada
   And dry grass singing
   But sound of water over a rock
   Where the hermit-thrush sings in the pine trees
   Drip drop drip drop drop drop drop
   But there is no water
Who is the third who walks always beside you?
When I count, there are only you and I together
But when I look ahead up the white road
There is always another one walking beside you
Gliding wrapt in a brown mantle, hooded
I do not know whether a man or a woman
—But who is that on the other side of you?
What is that sound high in the air
Murmur of maternal lamentation
Who are those hooded hordes swarming
Over endless plains, stumbling in cracked earth
Ringed by the flat horizon only
What is the city over the mountains
Cracks and reforms and bursts in the violet air
Falling towers
Jerusalem Athens Alexandria
Vienna London
Unreal
A woman drew her long black hair out tight
And fiddled whisper music on those strings
And bats with baby faces in the violet light
Whistled, and beat their wings
And crawled head downward down a blackened wall
And upside down in air were towers
Tolling reminiscent bells, that kept the hours
And voices singing out of empty cisterns and exhausted wells.
In this decayed hole among the mountains
In the faint moonlight, the grass is singing
Over the tumbled graves, about the chapel
There is the empty chapel, only the wind’s home.
It has no windows, and the door swings,
Dry bones can harm no one.
Only a cock stood on the rooftree
Co co rico co co rico
In a flash of lightning. Then a damp gust
Bringing rain
Ganga was sunken, and the limp leaves
Waited for rain, while the black clouds
Gathered far distant, over Himavant.
The jungle crouched, humped in silence.
Then spoke the thunder
DA
Datta: what have we given?
My friend, blood shaking my heart
The awful daring of a moment’s surrender
Which an age of prudence can never retract
By this, and this only, we have existed
Which is not to be found in our obituaries
Or in memories draped by the beneficent spider
Or under seals broken by the lean solicitor
In our empty rooms
DA
Dayadhvam: I have heard the key
Turn in the door once and turn once only
We think of the key, each in his prison
Thinking of the key, each confirms a prison
Only at nightfall, aethereal rumours
Revive for a moment a broken Coriolanus
DA
Damyata: The boat responded
Gaily, to the hand expert with sail and oar
The sea was calm, your heart would have responded
Gaily, when invited, beating obedient
To controlling hands
                                    I sat upon the shore
Fishing, with the arid plain behind me
Shall I at least set my lands in order?
London Bridge is falling down falling down falling down
Poi s’ascose nel foco che gli affina
Quando fiam uti chelidon—O swallow swallow
Le Prince d’Aquitaine à la tour abolie
These fragments I have shored against my ruins
Why then Ile fit you. Hieronymo’s mad againe.
Datta. Dayadhvam. Damyata.
                  Shantih     shantih     shantih
With respect.

25 Editing Tips for Tightening Your Copy:

Wow, it took more than a year to get into the editing part. Well, this is the 400th post.

Why am I saying???

Because quite often, at recent times I started and doing editing part bit by bit. Of course, I’m not good. I knew it. But I have to keep engaging. I cannot neglect or I should not give in to anyone, strategically. I personally don’t feel that’s good. I would like to edit.

I would love to correct something and I will fix it.

Writing is a part. But editing is a different part. I started understanding, whenever I write, I need to edit as good as. Over the last 50 posts, after I wrote, I will started rereading, spellchecks, grammatical errors.

I started researching on editing. I got 25 editing tips for tightening your copy.

Each one of the tips has such a good body paragraph. So, I could not copy and paste everything. Sometimes, I do. But sorry not quite often. I will paste the source link down below. I sincerely encourage you all to visit further.

25-tips-checklist1-768x1304

 

SOURCES: https://thewritelife.com/edit-your-copy/

 

With respect.

 

 

 

10 Best Data Science Books for Beginners and Advanced Data Scientist [Updated]:

By Ramya Shankar 18-22 minutes to read.

Sorry to say it again.

We all knew, “data is the new oil.”

Every organization preserving and securing their data. Even more, several organizations recruiting data scientists and data analysts to make their data effectively. And with the data, they create a long term impact on an organization. The decisions that are driven by the data too.

I’m passionate about the data. That’s why I was pursuing a data scientist course last January. So, I have to admit quite professionally and genuinely. I’m not much clear about the data collection methods and analysing the data patterns. I’m not from a coding background at all. But I have curiosity. I’m just working every day. I’m flexing my brain to learn a bit more.

I agree. It’s a long and tough journey. But it doesn’t mean, its impossible right!

Finally, not finally. Sorry, I need to attach an inspirational pic for us. And I need to conclude in a line. Then I will come to the content.

unnamed

So, everywhere I see books to learn. I’m looking forward to learn a bit lot. Let’s seek constantly.

I will paste the source link down below. I sincerely encourage you all to visit further. Also,the author had added bonus books too. Totally 22 books. Let’s look at it. Start reading.

About the Author:

A cheerful, full of life and vibrant person, I hold a lot of dreams that I want to fulfill on my own. My passion for writing started with small diary entries and travel blogs, after which I have moved on to writing well-researched technical content. I find it fascinating to blend thoughts and research and shape them into something beautiful through my writing.

Apart from the fact that Data Science is one of the highest-paid and most popular fields of date, it is also important to note that it will continue to be more innovative and challenging for another decade or more. There will be enough data science jobs that can fetch you a handsome salary as well as opportunities to grow.

That said, there is nothing better than reading data science books to get the ball rolling.

Learning data science through books will help you get a holistic view of Data Science as data science is not just about computing, it also includes mathematics, probability, statistics, programming, machine learning and much more.

Data Science Books

Here are some of the best books that you can read to better understand the concepts of data science –

  1. Head First Statistics: A Brain-Friendly Guide

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Just like other books of Headfirst, the tone of this book is friendly and conversational. The book covers a lot of statistics starting with descriptive statistics – mean, median, mode, standard deviation – and then go on to probability and inferential statistics like correlation, regression, etc… If you were a science or commerce student in school, you may have studied all of it, and the book is a great start to refresh everything you have already learned in a detailed manner. There are a lot of pictures and graphics and bits on the sides that are easy to remember. You can find some good real-life examples to keep you hooked on to the book. Overall a great book to begin your data science journey.

You can buy it here.

  1. Practical Statistics for Data Scientists

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If you are a beginner, this book will give you a good overview of all the concepts that you need to learn to master data science. The book is not too detailed but gives good enough information about all the high-level concepts like randomization, sampling, distribution, sample bias, etc… Each of these concepts is explained well and there are examples along with an explanation of how the concepts are relevant in data science. The book also surprises one with a survey of ML models.

This book covers all the topics that are needed for data science. It is a quick and easy reference, however, is not sufficient for mastering the concepts in-depth as the explanations and examples are not detailed.

You can buy it here.

  1. Introduction to Probability

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If you are from a math background in school, you might remember calculating the probability of getting a spade or heart from a pack of cards and so on.

This is perhaps the best book to learn about probability. The explanations are pretty neat and resemble real-life problems. If you have studied probability in school, this book is a must-have to further your knowledge of the basic concepts. If you are going to learn probability for the first time – this book can help you build a strong foundation in the core concepts, though you will have to work for a little longer with the book.

The book has been one of the most popular books for about 5 decades and that is one more reason why it should definitely be on your bookshelf.

You can buy it here.

  1. Introduction to Machine Learning with Python: A Guide for Data Scientists

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This is a book that can get you kick-started on your ML journey with Python. The concepts are explained as if to a layman and with sufficient examples for a better understanding. The tone is friendly and easy to understand. ML is quite a complex topic, however, after practicing along with the book, you should be able to build your own ML models. You will get a good grasp of ML concepts. The book has examples in Python but you wouldn’t need any prior knowledge of either maths or Programming languages for reading this book.

This book is for beginners and covers basic topics in detail. However, reading this book alone won’t be sufficient as you get deeper into ML and coding.

You can buy it here.

  1. Python Machine Learning By Example

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As the name says, this book is the easiest way to get into machine learning. The book gets you started with Python and machine learning in a detailed and interesting way with some classy examples like the spam email detection using Bayes and predictions using regression and tree-based algorithms. The author shares his experiences in the various areas of ML such as ad optimization, conversion rate prediction, click fraud detection, etc. which beautifully adds to the reading experience.

Though the book covers the basics of Python, you might want to start the book after you gain some basic knowledge of Python. The book will help you through the process of setting up the required software until the creation, update, and monitoring of models. Overall, a great book for beginners as well as advanced users.

You can buy it here.

  1. Pattern recognition and machine learning

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This book is for all age groups, whether you are an undergraduate, graduate or advanced level researcher, there is something for everyone. If you have a Kindle subscription, this book will cost you nothing. Get the international edition that has colorful pictures and graphs making your reading experience totally worth it.

Coming to the content, this is one book that covers machine learning inside out. It is thorough and explains the concepts with examples in a simple way. Few readers could find some of the terms tough to understand but you should be able to get through using other free resources like web articles or videos. The book is a must-have if you are serious about getting into machine learning, especially the mathematical (data analytics) part is exhaustive in nature.

Though you can use the book for self-learning, it would be a better idea to read it alongside some machine learning courses.

You can buy it here.

  1. Python for data analysis

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True to its name, the book covers all the possible methods of data analysis. It is a great start for a beginner and covers basics about Python before moving on to Python’s role in data analysis and statistics. The book is fast-paced and explains everything in a super simple manner. You can build some real applications within a week of reading the book. This book can also give you a guideline or be a reference for the topics that you will be otherwise lost for when you search for online courses.

With focussed learning of both Python and data science, this book gives you a fair idea of what you can expect by being a data analyst or data scientist when you actually start working. The author also gives a lot of references in the book and points to useful resources that you will enjoy going through. Overall, a well-organized book with a thorough explanation of data analysis concepts.

You can buy it here.

  1. Naked statistics

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This book brings out the beauty of statistics and makes statistics come alive. The tone is witty and conversational. You will not get bored reading this book or feel the heaviness of math! The author explains all the concepts of statistics – basic and advanced with real-life examples. The book starts with very basic stuff like the normal distribution, central theorem and goes on to complex real-life problems and correlating data analysis and machine learning.

While the book explains the basics well, it will be good to have some prior knowledge of statistics with some of these courses, so that you can quickly get on with the book.

You can buy it here.

  1. Data Science and big data analytics

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This book gently introduces big data and how it is important in today’s digitally competitive world. The whole data analytics lifecycle is explained in detail along with case study and appealing visuals so that you can see the practical working of the entire system. The structure and flow of the book are very good and well organized. You can easily understand the entire big picture of how analytics is done as each step is like one chapter in the book. The book includes clustering, regression, association rules and much more along with simple, everyday examples that one can relate to. Advanced analytics using MapReduce, Hadoop, and SQL are also introduced to the reader.

If you are planning to learn data science with R, this is the book for you.

You can buy it here.

  1. R for data science

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Another book for beginners who want to learn data science using R. R with data science explains not just the concepts of statistics but also the kind of data you would see in real life, how to transform it using the concepts like median, average, standard deviation etc. and how to plot the data, filter and clean it. The book will help you understand how messy and raw real data is and how it is processed. Transformation of data is one of the most time-consuming tasks and this book will help you gain a lot of knowledge on different methods of transforming data for processing so that meaningful insights can be taken from it. If you want to learn R before you start with the book, you can do so with simple online courses, however, the book has enough basics covered so that you can start off right away.

You can buy it here.

Bonus Data Science Books

Here We are listing a few more good books which you might be interested in:

  1. Inflection point

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This is not a technical book. However, since you have decided to move into Data science career path, it will be necessary to know why data science and big data holds such an important place today. The book is written from a business perspective and offers a lot of insight into how all the technologies like cloud, big data, IT, mobility, infrastructure, and others are transforming the way businesses work today along with interesting stories and personal experiences to share. The changing times and how we should cope with it are described beautifully in this book.

It is a good read and will keep you motivated during your data science learning journey.

You can buy it here.

  1. Storytelling with data

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Anything told as a story and shown as graphics fit into our mind easily and stays there permanently. The book is quite impactful and deals with the fundamental concepts of data visualization for you to understand how to make the most of the huge chunks of data available in the real world. The author’s way of explaining every concept is totally unique as he tells it in the form of a compelling story. You wouldn’t even realize how many concepts you can grasp in a day of reading the book – getting to know the context and audience, using the right graph for the right situation, recognizing and removing the clutter to get only the important information, utilize the most significant parts of the data and present them to users – all of these and more.

You can buy it here.

  1. Big Data – A revolution

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This is a must-have book, a primer to your big data, data science, and AI journey. It is not a technical book but will give you the whole picture of how big data is captured, converted and processed into sales and profits even without users like us knowing about it. It explains how companies are using our data and the information that we share over the internet is used to create new business innovations and solutions that make our lives easier and connect all of us. It also talks about the risks and implications involved in doing so, and how security measures are placed to avoid breach or misuse of data. There are technical papers in the end that are quite helpful. A good, simple read for everyone.

You can buy it here.

  1. Practical data science with R

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This is a medium level book, a good balance of basic principles and advanced data science principles. The keen focus is on business demands which is what makes the book very practical and interesting. It also explains statistics thoroughly which is one of the foundations of data science. Most books just explain how things are done – this book explains how and why! That helps motivate the readers to get into deep learning and machine learning. This is a good book for beginners and advanced level data scientists alike. It gets tougher as the advance of the topic but you can follow most of the book easily.

You can buy it here.

  1. The data science handbook

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This is an advanced book. If you have a little knowledge about statistics and data science through other books or tutorials, you will be able to appreciate the content of the book. It is not a purely technical book but a quick reference as it contains information in the form of questions and answers from various leading data scientists. The questions flow in an organized manner and help you understand each aspect of data science like data preparation, the importance of big data, the process of automation and how data science is the future of the digital world. The book lacks real case-studies though, however, if you have a business mindset, you will get to know a lot of strategies and tips from renowned data scientists who have been there, done that.

You can buy it here.

  1. Business analytics – the science of data-driven decision making

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This is an awesome in-depth book that explains the theory as well as practical applications to give wholesome knowledge. The author approaches the topics with subtlety and presents many case studies that are easy to understand, comprehend and follow. The book has everything from economics, statistics, finance and all you need to start learning data science. The book has been written with a lot of effort and experience and the way insights have been presented shows the same. It includes statistical and analytical tools, machine learning techniques and amalgamates basic and high-level concepts very well. You will also learn about scholastic models and six sigma towards the end of the book.

You can buy it here.

  1. Data mining techniques

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A wonderful book that explains data mining from scratch. So much so, that you need not be a computer science graduate to understand this book. It starts with explaining about the digital age, data mining and then moves to explain the kinds of data that can be mined, the patterns that can be mined, for example, cluster analysis, predictive analysis, correlations, etc., and the technologies that are used – statistics, machine learning, and database. The book is purely technical and you can go step-by-step to fully enjoy the book. The book is detailed – a must-have on your collection.

It has a lot of basic and advanced techniques for classification, cluster analysis and also talks about the trends and on-going research in the field of data mining.

You can buy it here.

  1. Thinking with data

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This is a small book that can be read along with other reading materials and online courses. It provides a lot of useful insights and enables critical business thinking in the reader. It helps you relate to why things are happening the way they are. Through the chapters, you will learn how to ask good meaningful questions, note down the important details of an idea and get key information to focus on. It nicely covers data-specific patterns of reasoning. The book will help you think ‘why’ and not just ‘how’. It covers what is called as CoNVO – context, needs, vision, and outcome.

You can buy it here.

  1. Machine learning with PySpark

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The book covers in detail about machine learning models, NLP (Natural language processing) applications and recommender systems using PySpark. It helps you understand the real-world business challenges and solve them. It covers linear regression, decision tree, logistic regression, and other supervised learning techniques. This book will enrich your knowledge greatly especially if you don’t just read it, rather work with the book and practice. You will also be able to appreciate the rich libraries of PySpark that are ideal for machine learning and data analysis. A great book to learn recommender systems using Spark – neat and simple.

You can buy it here.

  1. Generative Deep learning

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The book is like any other fiction book that keeps you hooked up till the last page. If you have read Harry Potter, you will know what we are talking about. The author has done an exceptional job in penning all the concepts in the form of stories that are easy to comprehend. The subjects of statistics and intuitive learning are a bit dry otherwise and this book does its best to make it as interactive and interesting as possible. If you read other books, you will realize how complex neural networks and probability are. This book makes it simple. Before starting the book, familiarise yourself with Python through some courses or tutorials. One of the best books for deep learning techniques from scratch.

You can buy it here.

  1. Data Science for business

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Purely business-oriented, this is one book to start with if you are not able to make up your mind into the field of data science. It clearly explains why you should learn data science and why it is the right choice for you. There are beautiful examples like the recommendation system, telecom churn rate, automated stock market analysis and more. The book keeps you motivated. It is not a book that will preach though. It is practical and gives you enough references to start with your technical journey too. The book emphasizes on discovering new business cases rather than just processing and analyzing data.

Check out a preview of the book on Amazon to know the concepts that are taken up in the book.

You can buy it here.

  1. Designing data-intensive applications

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Last, but not least, this book helps understand the architecture of today’s data systems and how they can be fit into applications that are data-driven and data-intensive. It doesn’t go into depth on management, security, installation and other things but explains data retrieval, database systems and fundamental concepts at length. This book is for you if you are an architect. The author discusses various aspects of designing database and data solutions and gives loads of other resources too (at the end of every chapter!) for you to further your knowledge on the topic.

You can buy it here.

More to go….

There are hundreds or more books related to data analytics and data science and don’t be overwhelmed with the huge chunk of books. You don’t have to read them all. We have carefully selected these and you should be able to build real-world models and get in-depth knowledge of data science with these books and the other resources mentioned in the blog. A few more reference books that can be helpful are Teach yourself SQL, too big to ignore, the hundred-page machine learning book, communicating data with Tableau and data analytics made accessible. Start your data science journey with any of the 22 books we have suggested and let us know how you liked reading them!

 

SOURCES: https://hackr.io/blog/data-science-books

 

With respect.

 

 

 

 

The 7 best deep learning books you should be reading right now:

Yesterday, I felt bad. I need to attach the picture of all the three. AI, ML, and DP. I missed it. I forget it. Sorry. Also, I would like to the AI books that I shared in last December. Please have a look and start reading it.

https://writerscommunity.home.blog/2019/12/11/15-best-books-on-ai/

 

875ca4a8-eb68-4005-8f70-7661c0fbfafe

Alright, today Deep Learning also comes. Because, as I said yesterday. We cannot avoid it. What I would say is, we must look forward to learn. I personally had a passion to learn. Although, I’m not a tech-savvy at all. I don’t feel bad. That’s okay.

Things are gonna be hard in the beginning.

I was totally struggled to find books for Deep Learning. Anyway, I got a very good books. So, have a look and start reading one by one.

About the Author:

Hi there, I’m Adrian Rosebrock, PhD. All too often I see developers, students, and researchers wasting their time, studying the wrong things, and generally struggling to get started with Computer Vision, Deep Learning, and OpenCV. I created this website to show you what I believe is the best possible way to get your start.

I gonna share the source down below. I sincerely encourage you all to visit further.

In today’s post I’m going to share with you the 7 best deep learning books (in no particular order) I have come across and would personally recommend you read.

Some of these deep learning books are heavily theoretical, focusing on the mathematics and associated assumptions behind neural networks and deep learning.

Other deep learning books are entirely practical and teach through code rather than theory.

And even other deep learning books straddle the line, giving you a healthy dose of theory while enabling you to “get your hands dirty” and learn by implementing (these tend to be my favorite deep learning books).

For each deep learning book I’ll discuss the core concepts covered, the target audience, and if the book is appropriate for you.

To discover the 7 best books for studying deep learning, just keep reading!

The 7 best deep learning books you should be reading right now

Before you choose a deep learning book, it’s best to assess your own personal learning style to ensure you get the most out of the book.

Start by asking yourself the following question:

How do I best learn? Do I like to learn from theoretical texts? Or do I like to learn from code snippets and implementation?

Everyone has their own personal learning style and your answers here will dictate which deep learning books you should be reading.

For me personally, I like to strike a balance between the two.

Deep learning books that are entirely theoretical and go too far into the abstract make it far too easy for my eyes to gloss over.

But on the other hand, if a deep learning book skips theory entirely and jumps straight into implementation, I know I’m missing out on core theoretical underpinnings that may help me approach a new deep learning problem or project.

In my opinion, a good deep learning book needs to carefully balance the two.

We need theory to help us understand the core fundamentals of deep learning — and at the same time we need implementation and code snippets to help us reinforce what we just learned.

deep_learning_books_goodfellow

  1. Deep Learning

It’s hard (if not impossible) to write a blog post regarding the best deep learning books without mentioning Goodfellow, Bengio, and Courville’s Deep Learning text.

This book is meant to be a textbook used to teach the fundamentals and theory surrounding deep learning in a college-level classroom.

Goodfellow et al.’s Deep Learning is entirely theoretical and written for an academic audience. There is no code covered in the book.

The book starts with a discussion on machine learning basics, including the applied mathematics needed to effectively study deep learning (linear algebra, probability and information theory, etc.) from an academic perspective.

From there, the book moves into modern deep learning algorithms and techniques.

The final part of Deep Learning focuses more on current research trends and where the deep learning field is moving.

I’ve personally read through this book twice, cover to cover, and have found it incredibly valuable, provided you have the mathematical/academic rigor required for such a textbook.

Deep Learning is available for online viewing for free from the book’s homepage. You can purchase a hardcopy of the text from Amazon.

You should read this deep learning book if…

  • You learn from theory rather than implementation
  • You enjoy academic writing
  • You are a professor, undergraduate, or graduate student doing work in deep learning

deep_learning_books_nielsen-300x239

  1. Neural Networks and Deep Learning

My second theory-based deep learning (e)book recommendation is Neural Networks and Deep Learning by Michael Nielsen.

The book does include some code but it’s important to underline the “some” — there are a total of seven Python scripts accompanying the book, all discussing a various fundamental machine learning, neural network, or deep learning technique on the MNIST dataset. The implementations are not the most “exciting” in the world, but they will help demonstrate some of the theoretical concepts in the text.

If you are new to machine learning and deep learning but are eager to dive into a theory-based learning approach, Nielsen’s book should be your first stop.

The book is a much quicker read than Goodfellow’s Deep Learning and Nielsen’s writing style combined with occasional code snippets makes it easier to work through.

You should read this deep learning book if…

  • You are looking for a theory-based deep learning text
  • Are new to machine learning/deep learning and want to approach the field from a more academic standpoint

deep_learning_books_chollet

  1. Deep Learning with Python

Francois Chollet, Google AI researcher and creator of the popular Keras deep learning library, published his book, Deep Learning with Python in October 2017.

Francois’ book takes a practitioner’s approach to deep learning. Some theory and discussion is included, but for every few paragraphs of theory, you’ll find a Keras implementation of the technique.

One of my favorite aspects of this book is how Francois includes examples for deep learning applied to computer vision, text, and sequences, making it a well rounded book for readers who want to learn the Keras library while studying machine learning and deep learning fundamentals.

I found Francois’ writing to be clear and accessible. His additional commentary on deep learning trends and history is phenomenal and insightful.

It’s important to note that this book is not meant to be a super deep dive into deep learning. Instead, it’s primary use is to teach you (1) the fundamentals of deep learning (2) through the Keras library (3) using practical examples in a variety of deep learning domains.

You should read this deep learning book if…

  • You are interested in the Keras library
  • You “learn by doing/implementing”
  • You want a quick understanding of how deep learning is applied to various fields, such as computer vision, sequence learning, and text

deep_learning_books_geron

  1. Hands-On Machine Learning with Scikit-Learn and TensorFlow

When I first purchased a copy of Aurélien Géron’s Hands-on Machine Learning with Scikit-Learn and TensorFlow, I wasn’t sure what to expect — had the title not included the word “TensorFlow” I may have breezed right by it, thinking it was only a basic introduction to machine learning.

But at the same time, appending the word “TensorFlow” to an already lengthy title that seems to focus on basic machine learning made me think it was a cheap marketing tactic to sell more copies — everyone is interested in deep learning, right?

Luckily, I was wrong — the book is a good read and the title shouldn’t deter you from reading through it.

Géron’s deep learning book is organized in two parts.

The first part covers basic machine learning algorithms such as Support Vector Machines (SVMs), Decision, Trees, Random Forests, ensemble methods, and basic unsupervised learning algorithms. Scikit-learn examples for each of the algorithms are included.

The second part then covers elementary deep learning concepts through the TensorFlow library.

You should read this deep learning book if…

  • You are new to machine learning and want to start with core principles with code examples
  • You are interested in the popular scikit-learn machine learning library
  • You want to quickly learn how to operate the TensorFlow library for basic deep learning tasks

deep_learning_books_kapoor

  1. TensorFlow Deep Learning Cookbook

If you like the “cookbook” style of teaching (little-to-no theory and lots of code), I would suggest taking a look at Gulli and Kapoor’s TensorFlow Deep Learning Cookbook.

This deep learning book is entirely hands-on and is a great reference for TensorFlow users.

Again, this book is not meant to necessarily teach deep learning, but instead show you how to operate the TensorFlow library in the context of deep learning.

Don’t get me wrong — you will absolutely learn new deep learning concepts, techniques, and algorithms along the way, but the book takes a heavy-handed cookbook approach: lots of code and explanations of what the code is doing.

My only criticism of the book is that there are some typos in the code snippets. This can be expected when writing a book that is entirely code focused. Typos happen, I can certainly attest to that. Just be aware of this when you are working through the text.

You should read this deep learning book if…

  • You have already studied the fundamentals of deep learning
  • You are interested in the TensorFlow library
  • You enjoy the “cookbook” style of teaching where code is provided to solve a particular problem but the underlying theory is not discussed

deep_learning_books_patterson

  1. Deep Learning: A Practitioners Approach

While most deep learning books that include code samples use Python, Adam Gibson and Josh Patterson’s Deep Learning: A Practitioners Approach instead use Java and the DL4J library.

Why Java?

Java is the most used programming language in large corporations, especially at the enterprise level.

The first few chapters in Gibson and Patterson’s book discuss basic machine learning and deep learning fundamentals. The rest of the book includes Java-based deep learning code examples using DL4J.

You should read this deep learning book if…

  • You have a specific use case where the Java programming language needs to be utilized
  • You work for a large company or enterprise organization where Java is primarily used
  • You want to understand how to operate the DL4J library

deep_learning_books_rosebrock

  1. Deep Learning for Computer Vision with Python

I’ll be completely honest and forthcoming and admit that I’m biased — I wrote Deep Learning for Computer Vision with Python.

That said, my book really has become one of the best deep learning and computer vision resources available today (take a look at this review and this one as well if you need an honest second opinion).

Francois Chollet, AI researcher at Google and creator of Keras, had this to say about my new deep learning book:

This book is a great, in-depth dive into practical deep learning for computer vision. I found it to be an approachable and enjoyable read: explanations are clear and highly detailed. You’ll find many practical tips and recommendations that are rarely included in other books or in university courses. I highly recommend it, both to practitioners and beginners. — Francois Chollet

And Adam Geitgey, the author of the popular Machine Learning is Fun! blog series, said this:

I highly recommend grabbing a copy of Deep Learning for Computer Vision with Python. It goes into a lot of detail and has tons of detailed examples. It’s the only book I’ve seen so far that covers both how things work and how to actually use them in the real world to solve difficult problems. Check it out! — Adam Geitgey

If you’re interested in studying deep learning applied to computer vision (image classification, object detection, image understanding, etc.), this is the perfect book for you.

Inside my book you will:

  • Learn the foundations of machine learning and deep learning in an accessible manner that balances both theory and implementation
  • Study advanced deep learning techniques, including object detection, multi-GPU training, transfer learning, and Generative Adversarial Networks (GANs)
  • Replicate the results of state-of-the-art papers, including ResNet, SqueezeNet, VGGNet, and others on the 1.2 million ImageNet dataset

Furthermore, I provide the best possible balance of both theory and hands-on implementation. For each theoretical deep learning concept you’ll find an associated Python implementation to help you cement the knowledge.

Be sure to take a look — and while you’re checking out the book, don’t forget to grab your (free) table of contents + sample chapters PDF of the book.

You should read this deep learning book if…

  • You are specifically interested in deep learning applied to computer vision and image understanding
  • You want an excellent balance between theory and implementation
  • You want a deep learning book that makes seemingly complicated algorithms and techniques easy to grasp and understand
  • You want a clear, easy to follow book to guide you on your path to deep learning mastery

Summary

In this post you discovered my seven favorite books for studying deep learning.

Have you purchased or read through one of these books? If so, leave a comment and let me know what you think of it.

Did I miss a book that you think should be on this list? If so, be sure to contact me or leave a comment.

 

SOURCE: https://www.pyimagesearch.com/2018/03/05/7-best-deep-learning-books-reading-right-now/

 

With respect.