Computers can’t LEARN… Right?!
Machine Learning is a branch of computer science that wants to stop programming computers using a list of detailed instructions. Instead, they are trying to implement high-level routines which tell 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
