Math for Machine Learning: Open Doors to Data Science and Artificial Intelligence - Softcover

Han, Richard

Softcover

ISBN 10: 057851270X ISBN 13: 9780578512709

Verlag: Richard Han, 2018

Inhaltsangabe

From self-driving cars and recommender systems to speech and face recognition, machine learning is the way of the future.  Would you like to learn the mathematics behind machine learning to enter the exciting fields of data science and artificial intelligence? There aren't many resources out there that give simple detailed examples and that walk you through the topics step by step.This book not only explains what kind of math is involved and the confusing notation, it also introduces you directly to the foundational topics in machine learning.  This book will get you started in machine learning in a smooth and natural way, preparing you for more advanced topics and dispelling the belief that machine learning is complicated, difficult, and intimidating.

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Críticas

"Your book is by far the best I’ve found for understanding the derivations of machine learning algorithms. I love that you don’t skip steps and that you provide clear examples."--Robert H.

Reseña del editor

From self-driving cars and recommender systems to speech and face recognition, machine learning is the way of the future.  Would you like to learn the mathematics behind machine learning to enter the exciting fields of data science and artificial intelligence? There aren't many resources out there that give simple detailed examples and that walk you through the topics step by step.This book not only explains what kind of math is involved and the confusing notation, it also introduces you directly to the foundational topics in machine learning.  This book will get you started in machine learning in a smooth and natural way, preparing you for more advanced topics and dispelling the belief that machine learning is complicated, difficult, and intimidating.

Details zur Ausgabe

• Verlag: Richard Han
• Erscheinungsdatum: 2018
• Sprache: Englisch
• ISBN 10: 057851270X
• ISBN 13: 9780578512709
• Einband: Tapa blanda
• Anzahl der Seiten: 154
• Kontakt zum Hersteller: Nicht verfügbar