Book of the month: Pattern Recognition and Machine Learning review

Our rating: ★★★★☆

This book is one of my first Data Science books I bought and one of the books I personally use most often. In this Pattern Recognition and Machine Learning review, I will give you my opinion on this book. Most of the core concepts of Data Science are discussed in this book, ranging from Stochastic Gradient Descent to Neural Networks and are explained in clear and understandable English. Some of the courses I followed were hard to follow, but most of the times, I could look up related material in this book which explained it in simple text with many examples. There are also plenty of exercises to help you through a topic and it builds up nicely. It explains nearly all pattern recognition or machine learning concepts and offers an comprehensive introduction to the fields of computer science, data mining and computer vision. Besides that, it sheds also lights on topics like probability theory in which many probability distributions and graphical models are explained. The great thing is that no previous knowledge of pattern recognition is assumed. So for beginners, advanced undergraduates or first year PhD students, students as well as researchers, researchers and practitioners, this book is an absolutely must-have. For more advanced Data Scientist, this book is great reference material. Make sure to buy this book now and add it to your collection!

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Kevin Jacobs

Kevin Jacobs

Kevin Jacobs is a certified Data Scientist and blog writer for Data Blogger. He is passionate about any project that involves large amounts of data and statistical data analysis. Kevin can be reached using Twitter (@kmjjacobs), LinkedIn or via e-mail: