• Machine Learning with Python

  • 2 Manuscript in 1: Complete Guide to Learning Machine Learning & What You Need to Know About Data Science
  • By: David Park
  • Narrated by: Matthew Kinsey, Shane Makena
  • Length: 6 hrs and 42 mins
  • 5.0 out of 5 stars (15 ratings)

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Publisher's Summary

It is not necessary to work on the projects associated with your job profile; you can work overtime by working on some projects which are not related to your job profile but go perfectly with your skill sets. It would lead to having a good impression on your boss, which would further lead to promotions. It might lead to a change in your role in the organization. This would lead you to the road map of your career in this field. 

Python is a high-level scripting language. It is easy to learn and more robust than other languages because of its dynamic nature and simple syntax, which allows small lines of code. Indentation and object-oriented, functional programming make it simple. Such advantages of Python makes it different from another language, and that's why Python is preferred for development in companies mostly. 

In industries, machine learning using Python has become popular. This is because it has standard libraries that are used for scientific and numerical calculations. Also, it can be operated on Linux, Windows, Mac OS, and UNIX.

What you will gain in this book:

  • What is meant by machine learning?   
  • A short history of machine learning   
  • Machine learning - automation within a knowledge   
  • The challenges of machine learning   
  • Advantages and disadvantages of machine learning language   
  • Machine learning in robotics   
  • Machine learning applications   
  • Machine learning algorithms   
  • How machine learning is changing the world - and your everyday life

Machine learning is a new, trending field these days and is an application of artificial intelligence. The main aim of machine learning is to create intelligent machines that can think and work like human beings.

©2020 David Park (P)2020 David Park

What listeners say about Machine Learning with Python

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Easy for a beginner to follow,

I used this audio book when I was first learning Machine Learning and, years later, I still reference this audio book. It is well written, well organized, easy for a beginner to follow, with hands-on examples, and thorough enough to be valuable to advanced practitioners.

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It's all terribly practical and understandable.

This audio book walks thru a TON of ML algorithms and applications with example code but the code is so succinct that it's not really a programming audio book as much as a crash course in some ML math libraries available for Python, what the algorithms do and when to use them. It doesn't get into the math but it does give clear examples and explanations of when to use each algorithm and how. It's all terribly practical and understandable.

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Highly recommended!

This audio book helped me immensely with understanding and using a lot of different kinds of machine learning models. Highly recommended!

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The most complete python based ML audio book

A classic. Clearly demarcated to sklearn based non-deep learning ML section and the deep learning portion which goes in-depth into Keras and tf. A good amount of material on deep reinforcement learning as well.

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Choose it for ML

If you want a audio book to illustrate ML algorithms with TF implementation, you can choose this one.

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Good

Excellent audio book to get into the most popular libraries for machine learning using python. Good examples and support.

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Easy to follow

The examples in the audio book are really good and easy to follow. I have been using this as a reference for my project. It’s worth every penny!

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Very practical

Wonderful audio book! Just what I expected. Very practical, hands-on like the title says. I have the first edition and I don’t regret one single bit buying the second. A must for any machine learning practitioner!

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Must Have Text

This is one of the audio books every good data scientist has to have. Everyone and his mother is calling himself a “Data Scientist” and they have no practical experience, no math background, and no conception of how to use data science. This audio book solves a lot of those problems or at least you can spot the phonies. It is one of the best data science audio books ever written.

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Like it!

What I really like about this is a audio book is that the author knows how to explain ML concepts by solving a real-world example problem, as opposed to just explaining the theory.