Deep Learning with Python, 2nd Edition
- 14h 56m 4s
- Derek Dysart, Francois Chollet
- Manning Publications
Deep Learning with Python has taught thousands how to put the full capabilities of deep learning into action. This extensively revised second edition introduces deep learning using Python and Keras and is loaded with insights for both novice and experienced machine learning practitioners. You’ll learn practical techniques that are easy to apply in the real world and important theory for perfecting neural networks.
About the technology
Recent innovations in deep learning unlock exciting new software capabilities, like automated language translation, image recognition, and more. Deep learning is quickly becoming essential knowledge for every software developer, and modern tools like Keras and TensorFlow put it within your reach - even if you have no background in mathematics or data science. This book shows you how to get started.
About the book
Deep Learning with Python (Second Edition) introduces the field of deep learning using Python and the powerful Keras library. In this revised and expanded new edition, Keras creator François Chollet offers insights for both novice and experienced machine learning practitioners. As you move through this book, you’ll build your understanding through intuitive explanations and clear examples. You’ll quickly pick up the skills you need to start developing deep learning applications.
- Deep learning from first principles
- Image classification and image segmentation
- Time series forecasting
- Text classification and machine translation
- Text generation, neural style transfer, and image generation
In this Audiobook
Chapter 1 - What is deep learning?
Chapter 2 - The mathematical building blocks of neural networks
Chapter 3 - Introduction to Keras and TensorFlow
Chapter 4 - Getting started with neural networks: Classification and regression
Chapter 5 - Fundamentals of machine learning
Chapter 6 - The universal workflow of machine learning
Chapter 7 - Working with Keras: A deep dive
Chapter 8 - Introduction to deep learning for computer vision
Chapter 9 - Advanced deep learning for computer vision
Chapter 10 - Deep learning for time series
Chapter 11 - Deep learning for text
Chapter 12 - Generative deep learning
Chapter 13 - Best practices for the real world
Chapter 14 - Conclusions