Machine learning is a branch of artificial intelligence (AI) that allows computers to learn and improve on their own without having to be explicitly programmed. Machine learning is concerned with the creation of computer programmed that can access data and learn on their own. The book includes code examples for all of the ideas you'll need as a data scientist, from programming to statistics to probability to Big Data. This is the book you need to own and read if you're a newbie data scientist.
How should you create your Owen project ?
Random forests and support vector machines are two techniques you'll almost certainly come across when working on a project. There are also code snippets from scikit-learn. Instead of copying them into your project by hand, open this book and turn to the chapter that discusses the algorithm you'll be using.
Every machine learning algorithm is covered in detail in this book, both in terms of theory and application. You'll have a lot more confidence now that you know what goes on behind the scenes of your models. There's also advanced content, such as autoencoders and reinforcement learning. I strongly advise you to use this book as a learning aid in your early years.
