"Python Deep Learning" is based on the deep learning framework, introduces the basic knowledge and common methods of machine learning, and comprehensively and meticulously provides the principles of machine learning operations and its practical steps under the deep learning framework.
The book has 16 chapters in total, which introduce the basic knowledge of deep learning, deep learning frameworks and their comparisons, basic knowledge of machine learning, basics of deep learning frameworks (taking PyTorch as an example), logistic regression, multi-layer perceptron, convolutional neural network and computer vision, neural network and natural language processing, and 8 practical cases.
This book closely combines theory and practice, and I believe it can provide readers with useful learning guidance. "Python Deep Learning" is suitable for beginners of Python deep learning, practitioners of machine learning algorithm analysis, and teachers and students of computer science, software engineering and other related majors in colleges and universities.
Reader comments
This book is very suitable for new mothers like me. It has comprehensive content and easy-to-understand language. By reading this book, I not only understood the basics of deep learning, but also learned how to apply theory into practice. The cases in the book are very interesting and gave me a deeper understanding of machine learning and deep learning. I recommend it to everyone!
It's a very good book. I think it's quite suitable as an introduction to deep learning.
This book is very suitable for new mothers like me. It has comprehensive content and easy-to-understand language. By reading this book, I not only understood the basics of deep learning, but also learned how to apply theory into practice. The cases in the book are very interesting and gave me a deeper understanding of machine learning and deep learning. I recommend it to everyone!
It's a very good book. I think it's quite suitable as an introduction to deep learning.