Machine Learning: Fundamental Algorithms for Supervised and Unsupervised Learning With Real-World Applications (Advanced Data Analytics Book 1)

✍ Scribed by Joshua Chapmann

Tongue: English
Leaves: 103
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

Computers can't LEARN... Right?!

Machine Learning is a branch of computer science that wants to stop programming computers using a detailed list of commands to follow blindly. Instead, their aim is to implement high-level routines that teach computers how to approach new and unknown problems – these are called algorithms.

In practice, they want to give computers the ability to Learn and to Adapt.

We can use these algorithms to obtain insights, recognize patterns and make predictions from data, images, sounds or videos we have never seen before – or even knew existed. Unfortunately, the true power and applications of today’s Machine Learning Algorithms remain deeply misunderstood by most people.

Through this book I want fix this confusion, I want to shed light on the most relevant Machine Learning Algorithms used in the industry. I will show you exactly how each algorithm works, why it works and when you should use it.

Supervised Learning Algorithms

K-Nearest Neighbour
Naïve Bayes
Regressions

Unsupervised Learning Algorithms:

Support Vector Machines
Neural Networks
Decision Trees

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