Description
Deep Learning for Complete Beginners: A Python-Based Introduction is for complete beginners in machine learning. It introduces fundamental concepts such as classes and labels, building a dataset, and what a model is and does before presenting classic machine learning models, neural networks, and modern convolutional neural networks. Experiments in Python - working with leading open-source toolkits and standard datasets - give the reader hands-on experience with each model and help them build intuition about how to transfer the examples in the book to their own projects.
This book is for people with no experience with machine learning and who are looking for an intuition-based, hands-on introduction to deep learning using Python.
About the Author
Ron Kneusel has been working in the machine learning industry since 2003 and has been programming in Python since 2004. He received a PhD in Computer Science from UC Boulder in 2016 and is the author of two previous books: Numbers and Computers and Random Numbers and Computers.
Reviews
"Practical Deep Learning with Python is the perfect book for someone looking to break into deep learning. This book achieves an ideal balance between explaining prerequisite introductory material and exploring nuanced subtleties of the methods described. The reader will come away with a solid foundational understanding of the content as well as the practical knowledge required to apply the methods to real-world problems. Deep learning will continue to enable many breakthroughs in artificial intelligence applications and this book covers all that is needed to springboard into this exciting field."
-Matt Wilder, longtime neural network practitioner and owner of Wilder AI, a deep learning consulting company
"Kneusel's book tackles machine learning (classification) fantastically, helping anyone with an interest to learn and turning that interest into a skillset for future machine learning projects."
-GeekDude, GeekTechStuff
Book Information
ISBN 9781718500747
Author Ron Kneusel
Format Paperback
Page Count 464
Imprint No Starch Press,US
Publisher No Starch Press,US
This book is for people with no experience with machine learning and who are looking for an intuition-based, hands-on introduction to deep learning using Python.
About the Author
Ron Kneusel has been working in the machine learning industry since 2003 and has been programming in Python since 2004. He received a PhD in Computer Science from UC Boulder in 2016 and is the author of two previous books: Numbers and Computers and Random Numbers and Computers.
Reviews
"Practical Deep Learning with Python is the perfect book for someone looking to break into deep learning. This book achieves an ideal balance between explaining prerequisite introductory material and exploring nuanced subtleties of the methods described. The reader will come away with a solid foundational understanding of the content as well as the practical knowledge required to apply the methods to real-world problems. Deep learning will continue to enable many breakthroughs in artificial intelligence applications and this book covers all that is needed to springboard into this exciting field."
-Matt Wilder, longtime neural network practitioner and owner of Wilder AI, a deep learning consulting company
"Kneusel's book tackles machine learning (classification) fantastically, helping anyone with an interest to learn and turning that interest into a skillset for future machine learning projects."
-GeekDude, GeekTechStuff
Book Information
ISBN 9781718500747
Author Ron Kneusel
Format Paperback
Page Count 464
Imprint No Starch Press,US
Publisher No Starch Press,US
