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Leonard Deep
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Data Science for Beginners: This Book Includes - Machine Learning for Beginners + Python Machine Learning for Beginners - Big Data Analytics, Data Science, Data Analysis and Programming Code Paperback – July 3, 2019

by Leonard Deep (Author)
3.2 out of 5 stars (19)
Have you ever wondered how speech recognition and search engines really work? Do you wish you could get a machine to do more of your tasks? Even if you are brand new to programming, you can learn how to use Python and Machine Learning to make your life easier or develop a satisfying career in a growth industry.


You probably use Machine Learning countless times daily. Your search engine or a chess app, the GPS that gives you turn-by-turn driving directions, an app that predicts the next word you want to type or translates your voice to text: they all use Machine Learning.

If you are interested in programming and want to understand Python and Machine Learning, the thoughtful, systematic approach to learning in this two-volume bundle will help you get started in this growing field even if you are a novice.

Machine Learning for Beginners covers the basic knowledge you need and explores all of the cool accomplishments this kind of programming language allows. It answers these and other questions:

  • What is data science and why is it important?
  • What is machine learning and what the benefits of this kind of programming?
  • What is the difference between machine learning and artificial intelligence?
  • What basics and building blocks do you need to know about machine learning?
  • How do supervised machine learning, unsupervised machine learning, and reinforcement machine learning differ?
  • What tips will help you the most out of machine learning?

Python Machine Learning for Beginners, the ultimate guide for newbies, provides easy-to-understand chapters to guide you through the early stages of Python programming, considered an excellent program choice for beginners. Topics include:

  • An introduction to Machine Learning
  • The main concepts of Machine Learning
  • The basics of Python for beginners
  • Machine Learning with Python
  • Data Processing, Analysis, and Visualizations
  • Case studies and much more!

Python Machine Learning for Beginners uses examples and exercises to help you retain the information. Machine Learning for Beginners provides the tools you need to enjoy the many benefits of using machine learning for some of your programming needs.

Scroll back up to the top of this page and hit BUY IT NOW to get your copy and start learning how to write your own machine learning programs.

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  1. Print length
    354 pages
  2. Language
    English
  3. Publication date
    July 3, 2019
  4. Dimensions
    6 x 0.89 x 9 inches
  5. ISBN-10
    1076939686
  6. ISBN-13
    978-1076939685
Next slide of product details
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Product details

  • Publisher ‏ : ‎ Independently published
  • Publication date ‏ : ‎ July 3, 2019
  • Language ‏ : ‎ English
  • Print length ‏ : ‎ 354 pages
  • ISBN-10 ‏ : ‎ 1076939686
  • ISBN-13 ‏ : ‎ 978-1076939685
  • Item Weight ‏ : ‎ 1.19 pounds
  • Dimensions ‏ : ‎ 6 x 0.89 x 9 inches
  • Best Sellers Rank: #12,481,320 in Books (See Top 100 in Books)
  • Customer Reviews:
    3.2 out of 5 stars (19)

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Leonard Deep

Leonard Deep

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Customer reviews

3.2 out of 5 stars
19 global ratings

Top reviews from the United States

  • Amazon Customer
    1.0 out of 5 stars Poor grammar and little to no substance.
    Reviewed in the United States on June 1, 2021
    Verified Purchase
    Revised 6/1/21: This "book" is absolute garbage. Save your $ and move on....

    Like others I neglected to read the reviews. Too late now but there's $9.99 I'll never get back. The grammar is terrible and hard to follow. More hype than substance and certainly not the level of content I wanted. Here's a great example of the author's "Thanks Captain Obvious" type of writing: "As our world started to enter into a new era that has a lot of big data, it became more prevalent that the need to store this data was going to grow as well". Most of the writing in this book is similar to that example. Save your $, find another book.
    One person found this helpful
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  • Jimster716
    3.0 out of 5 stars Fake reviews?
    Reviewed in the United States on July 29, 2019
    I am considering this book but the reviews have turned me off. Several reviewers state that the book is great for their new jobs as data scientists after toiling for years as software engineers. Coincidence? They also have questionable English skills, grammar and vocabulary that are consistent with each other and a couple of reviewers both used the word, "peruser," which is not part of the normal English vernacular and not in the correct context. Therefore, it is easy to surmise that several of these reviews are foreign, fake, and possibly submitted to sway the 2020 elections. Hahaha
    10 people found this helpful
    Helpful
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  • Michael Hoyt
    1.0 out of 5 stars Poorly Written
    Reviewed in the United States on December 26, 2019
    I got this book for Christmas from my wife. I put it on my wish list and now I wish I would've read the 1-star reviews. I completely concur with the other 1-star reviews. It is unreadable. The book uses a very large font which means there's not nearly as much content as the book's 346 pages might suggest. The grammar is horrendous. I could get passed that and try to extract some value from this book but its just not possible to read. Its like being asked to proofread something for someone when their work isn't even ready for proofreading. Its actually 3 books in one. So each book is actually only around 100 pages.

    Full disclosure, I only read the first 10-15 pages but that was enough. Its going back. The 5 star reviews are really hard to reconcile.
    2 people found this helpful
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  • Christopher Bailey
    1.0 out of 5 stars It's Pretty Clear...
    Reviewed in the United States on August 30, 2019
    That most of the reviews on here are fake (just punch the URL into Fakespot) as another reviewer stated. On my search for a reputable intro into Data Science, I stumbled upon this book which had great reviews. It seemed legit until I started reading the intro. It is borderline unreadable. I don't know how books like this ever get published because the grammar is so, so bad. It reads as if it were written in another language and someone plugged it into Google Translate and then published it. Huge bummer. I'm just trying to find a decent book on Data Science using Python!
    6 people found this helpful
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  • Amazon Customer
    1.0 out of 5 stars Terrible book, avoid!
    Reviewed in the United States on October 18, 2019
    While I normally avoid writing review, I see it as my civil duty to write one here. Full disclosure: I have scientific training, including programming and statistics. I have read 17% of the book and did not manage to go any further. The language is terrible. Entire paragraphs consist of circular logic or can be boiled down to a simple sentence. In a few places there are obvious grammar error. Examples are so broad and high-level as to be entirely useless.
    In short: save your money and, more importantly, time. Search one of many on-line resources or a better book.
    4 people found this helpful
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Top reviews from other countries

  • Amazon Customer
    1.0 out of 5 stars Unable to obtain 'free' Kindle version promised
    Reviewed in the United Kingdom on July 30, 2019
    Verified Purchase
    Advertisement for this book indicates free Kindle version is provided with paperback. However, Kindle version charged at £9.99. Beware!
    Report
  • Zeno
    1.0 out of 5 stars Not at all worth to buy/read
    Reviewed in Germany on July 22, 2020
    Verified Purchase
    The book is poorly written and has not many useful information. There are way better books to read. The whole book rather seems to be like a poor blog post made into a book.

    If you want to get into data science read books like Data Mining from pang-ning tan, or sth comparable (depends on the detph of mathematics you want to learn, gradually increasing the difficulty and starting with sth like the above mentioned book is a good starting point I think)
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