From the book:"My aim is not provide a comprehensive history of cultural software in general, or media authoring software in particular. Nor do I aim to discuss all new creative techniques it enables across different cultural fields. Instead, I will trace a particular path through this history that will take us from 1960 to today and which will pass through some of its most crucial points."

    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

    It shows readers how to step back from coding to consider design strategies and attempt to get into the head of the designer.