Description

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If you are intrigued by machine learning topics and ready to demystify the topics of clustering, classification, curse of dimensionality, model training, validation and assessment then this book is for you. Apart from introducing the general topics, it dives deeper into selected algorithms, including K-means clustering, Self-Organizing Maps, Principal Component Analysis, Support Vector Machine and Logistic Regressions. Ideas are explained with lots of clarity using plenty of pictures, examples, and python code. This book not only introduces you to the key machine learning algorithms, it also motivates and empowers you to explore more. This book is for students, engineers, consultants, managers, educators and for everyone else who is interested in machine learning.