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Publisher's Summary

Master the world of machine learning - even if you’re a complete beginner.

Are you an aspiring entrepreneur? Or are you an amateur software developer looking for a break in the world of machine learning? Then this is the book for you.

Machine learning is the way of the future - and breaking into this highly lucrative and ever-evolving field is a great way for your career, or business, to prosper. Inside this guide, you’ll find simple, easy-to-follow explanations of the fundamental concepts behind machine learning, from the mathematical and statistical concepts to the programming behind them. 

With a wide range of comprehensive advice including machine learning models, neural networks, statistics, and much more, this guide is a highly effective tool for mastering this incredible technology.

Inside, you will:

  • Learn the fundamental concepts of machine learning algorithms, and their impact in resolving modern day business problems
  • Understand the four fundamental types of machine learning algorithm
  • Master the concept of “statistical learning”, a descriptive statistics-based machine learning algorithm
  • Dive into the development and application of six of the most popular supervised and unsupervised machine learning algorithms, with details on linear regression, logistic regression and more
  • Learn everything you need to know about neural networks and data pipelines
  • Master the concept of “general setting of learning”, a fundamental of machine learning development
  • Overview the basics, importance, and applications of data science with details on the “team data science process” lifecycle
  • And much more!

Covering everything you need to know about machine learning, now you can master the mathematics and statistics behind this field and develop your very own neural networks! Whether you want to use machine learning to help your business, or you’re a programmer looking to expand your skills, this book is a must-read for anyone interested in the world of machine learning. 

Buy now to discover how you can master machine learning today!

Scroll up and click the "buy now" button to get your copy!

©2019 Samuel Hack (P)2019 Samuel Hack

What listeners say about Machine Learning Mathematics

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  • Alexander B. Stevens
  • 25-10-2020

Energetic theory of machine learning mathematics

The future looks like it will be even more tech based than it is now with machines being almost indistinguishable from humans . Learn and the technique of teaching simple concepts in small steps .Amazing way of how he teaches.If you are in software development the author also believes knowing machine learning mathematics will give you that competitive edge you will need to develop some innovative technology.

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  • Charles Y. Velez
  • 25-10-2020

Mind-blowing learn a new language is by practicing

Good way to learn a programming language and is hard going at times,this book to help you break down the basics, including conditional and decision statements, list and tuples, and even input and loops but it gets you thinking of what and why we approach things in this way.

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  • Martin F. Bowser
  • 25-10-2020

Fantastic teaching technique machine Learning

It stands out among other audio books and is a complete resource for beginners and experts alike, and is an innovative for this. If you are looking for a clear, intriguing and fun reading about your approach to machine learning, this is an extraordinary for that. I highly recommend this to everyone.

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  • Randal J. Kirk
  • 25-10-2020

This approach to learning is the best

Teaches you how you should think while you follow the examples given in this. Slowly introducing you into topics, gradually getting harder and harder as you go. You are rewarded towards the middle with a test. The best kind of test, a fix the program kind of test. Thanks to the author.

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  • Joaquin A. Klima
  • 24-10-2020

It will teach you how to work with complex data

It is aimed at people with an intermediate level of knowledge in working with machine learning algorithms. It will teach you how to work with complex data. It is a step by step guide through a wide variety of machine learning concepts and techniques. Recommended.

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  • Curtis J. Cooper
  • 24-10-2020

Most reachable modern programming languages

Essentially touches on every topic you need to know and hits those topics from every angle. If you are a statistician who has barely touched any code, it uses Python, one of the the most reachable modern programming languages. If you are new to machine learning in general, it starts easy and goes all the way to advanced.

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  • Robert A. Quezada
  • 24-10-2020

Fast, pretty fun easy to understand

This was pretty fun as a beginner. I’ve always thought coding was too difficult for me to understand. While that is still mostly true, this was quite fun to read with exercises to try. It made coding seem simple and possible! I be able to do it all by myself, this definitely is a great reference.

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  • Henry H. Vargas
  • 24-10-2020

Tremendous variety of machine learning algorithms

It covers a wide variety of machine learning algorithms, and while it does include some math,focus like other on the topic. The math sections are involved, giving the formulas and basic information the various algorithms are based on, but most importantly it's accompanied by easier to understand explanations and pseudo code/actual code implementations

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  • Robert D. Hendrix
  • 24-10-2020

Cover most of recent main advancement in the field

General discussion of machine learning, including data preparation, visualization, splitting into train and test sets, model fitting, and evaluation As the name suggests, gives you a really hands-on experience on machine learning. This covers most of the recent main advancements in the field.

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  • Brandon G. Dean
  • 23-10-2020

Legit answer to the programming exercise available

A great deal of important vocabulary is weaved into the material.I wish that the legit answers to the programming exercises were available somewhere to compare my code with. I highly recommend this for anyone interested in learning data mining with self study.

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  • William D. Piercy
  • 25-10-2020

Will give you that competitive innovative edge

If you are in software development the author also believes knowing machine learning mathematics will give you that competitive edge you will need to develop some innovative technology. From someone new to the field I found that it explained certain concepts to clearly and really made me understand the fundamentals of the topic

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  • Alvin G. Williams
  • 25-10-2020

For Beginners,worth checking out if your advanced

Definitely aimed at beginners. People who have never coded. I have been programming for 10+ years, though, and was able to pick up this through in a couple hours and go off coding Python like I had been for years. Also, it didn't hurt that this was actually funny.

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  • Bobbie M. Alexander
  • 25-10-2020

Explain complex concepts in a natural and easy way

In this super bundle I think that the author did an excellent work, because everything is well explained, in simple language. His ability is to explain complex concepts in a natural and easy way. Believe me, If you want to start studying this fascinating world, this is the best gift you could give yourself.

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  • George T. Brook
  • 25-10-2020

Its attention to the mathematical theory

I'm very early on in the text, but the text is impressive in the breadth and depth of its coverage, along with its attention to the mathematical theory. The exercises are challenging, which makes the text a little tricky for self study.

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  • Gordon C. Hughes
  • 24-10-2020

Rapid development language with good tools

Now that the data science community has started building state of art tools for artificial intelligence. I prefer a rapid development language with good tools, test-first frameworks and solid software engineering practices as part of the culture. Thanks to the author for this valuable audio book.

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  • Edward C. Youngberg
  • 24-10-2020

Bagging an boosting & compares idea of collection

This section is on bagging an boosting and then compares the idea of a collection of weak learners like stubby random trees as a powerful tool the idea behind random forests. There are lots of examples where the cost of putting a label on a data example is too high, so an unsupervised method is a good call.

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  • Garland S. Larson
  • 24-10-2020

Bite sized chunks that introduce a new path

In a world where you have to have a full time job to live, to survive. Where that job probably isn't something you truly want to do. audio books like this are perfect. They are bite sized chunks that introduce a new path. A way to forge a new career in the after hours.

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  • Carolyn K. Joiner
  • 24-10-2020

Intuitive explanations of important algorithms.

Most importantly it's accompanied by easier to understand explanations and actual code implementations. I certainly hope the author continues to update and maintain this over time .As a bonus, a great way to get bootstrapped into advanced Python addressing. Could benefit from real-valued genetic algorithm chromosome examples.

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  • Lora N. Lovejoy
  • 24-10-2020

Audio book has hit all the tools you will need

The audio book has hit all the tools you will need to move to a more advanced components of data Mining. Learning about computer programming can seem intimidating. Check out this and find out what practical applications you can create with Python. Thanks to the author.

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  • Dianna T. Goodman
  • 23-10-2020

Awesome tips and tricks for new apps and features

Excellent for machine learning mathematics. Tips and tricks for new apps and features are what I really like from this, also it explains everything very well. Really this audio book is so helpful. Thanks to the author for this valuable information share with us.

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