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Summary

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 are 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 the "BUY" button to get your copy and start learning how to write your own machine learning programs.

©2019 Leonard Deep (P)2019 Leonard Deep

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Bland and basic

Rushes through concepts, very shallow! The author appears to only have a basic unwarranted of the subject!

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  • Harbard
  • 05-10-19

Great introductory book and Worth reading

This is the best machine learning book I have ever read!!! The author breaks things done into simple easy to understand components.It was entertaining and highly educational. I especially appreciated the effort made by the author to walk a newbie through installation of a new programming environment .. An elegantly composed book giving a decent broad comprehension.

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  • Alferd
  • 05-10-19

Machne Learning with Python will walk you

Machne Learning with Python will walk you through it all. I was able to learn way of implementing to areas I was trying to break through before with a lot of ease. It also walks you through how to use on a Cloud Environment, which is going to be an invaluable tool for your career if it's anywhere related to software.

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  • Momentary
  • 30-09-19

A difficult listen.

I'll admit that I am still only on chapter one, but it's already apparent to me that the author isn't a native English speaker, nor was the editor. Interesting topic, but very hard to understand even parts that should be easy.

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  • John
  • 09-12-19

Not what I was expecting

The machine learning portion was more on point for what I wanted. The rest was just code being dictated. Very hard to keep up with code. Needs some work sheets or something to accompany so the reader has a clue what’s going on.

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  • Roselen
  • 05-10-19

Data Science - Technical implementation tied

The institution strategy and goals need to be reflected in the procedures used to analyse the data base of the institution and the determination as to what data is relevant. The book discusses ways to obtain the data needed and the short term volatility in return to the company that can result. a valuable contribution to the understanding of Data Science.

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  • Jerin
  • 05-10-19

More impactful presentation of data

The concepts were well explained and supported with examples. The thought process described here applies to novices as well as professionals who are looking to stand out more with their style of presentation. The author shows the effect of simplicity and how aesthetics can make all the difference in getting a point across .

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  • Odila
  • 05-10-19

If you are interested in influencing with data

Cole's book and have made a tremendous impact on my storytelling with data skills. I have used her advice in this book to influence leaders and colleagues by telling stories with data vs just showing data. This book is definitely to keep forever .

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  • Rey
  • 05-10-19

Improve your data visualization skills

Good book, well written. If you turn data into reports - this book is for you. I learned a lot.This book is amazing and really highlights easy practical ways to use our understanding of how our brains process information, and how and where we focus to draw an audience to particular data.

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  • Morgan
  • 05-10-19

only expect it to get better and better

I'm halfway through the book and it has already proven to be thoroughly valuable. I only expect it to get better and better. continually backs up data viz theory with real-life samples, contrasting the good with the bad. I've already implemented many of these data viz best practices in my line of work.improve the way you visualize your data .

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  • Ammy
  • 05-10-19

Excellent introductory and Very useful overview

This is an excellent introductory-intermediate level Machine Learning book. You will get more from the book if you have a some knowledge of python. It teaches to set-up environment and work with a sample data set and This is review is from the perspective of someone who knows a little python and had little knowledge of machine learning,