Books
William Sullivan

Python Machine Learning Illustrated Guide For Beginners & Intermediates

Python Machine Learning Illustrated Guide For Beginners  & Intermediates

 Machines Can Learn ?!

Automation and systematization is taking over the world. Slowly but surely we continuously see the rapid expansion of artificial intelligence, self-check out cash registers, automated phone lines, people-less car-washes, etc. The world is changing, find out how python programming ties into machine learning so you don't miss out on this next big trend!

This is your beginner's step by step guide with illustrated pictures!

Let's face it, machine learning is here to stay for the foreseeable future and will impact the lives billions worldwide! Drastically changing the world we live in the most fundamental ways, from our perceptions, life-style, thinking and in other aspects as well.

What You Will Learn

 Linear & Polynomial Regression

Support Vector Machines

Decision Trees

Random Forest

KNN Algorithm

Naive Bayes Algorithm

Unsupervised Learning

Clustering

Cross Validation

Grid Search

And, much, much more!

If you want to learn more about python machine learning it is highly recommended you start from the ground up by using this book. Normally books on this subject matter are expensive! Why not start off by making a small and affordable investment with your illustrated beginners guide that walks you through python machine learning step by step

 Why choose this book?

Addresses Fundamental Concepts

Goes Straight To The Point, No fluff or Nonsense

Practical Examples

High Quality Diagrams

“Noob friendly” (Good For Beginners & Intermediates)

Contains Various Aspects of Machine Learning

Endorses Learn “By Doing Approach”

Concise And To The Point

I been working tirelessly to provide you quality books at an affordable price. I believe this book will give you the confidence to tackle python machine learning at a fundamental level.

What are you waiting for? Make the greatest investment in YOUR knowledge base right now.

Buy your copy now!
194 printed pages
Original publication
2019
Publisher
PublishDrive

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Quotes

    Xeniia Ivanchenkohas quoted4 months ago
    In mathematical terms, you have input variable X and output variable y, and you have to find a function that captures relationship between the two i.e.
    y= f(X)
    Xeniia Ivanchenkohas quoted4 months ago
    Tom Mitchel from Carnegie Mellon University defined machine learning in mathematically understandable terms as in 1997. He said:
    “A computer program is said to learn from experience E with respect to some task T and some performance measure P, if its performance on T, as measured by P, improves with experience E.”

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