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The Deep Learning with Keras Workshop: An Interactive Approach to Understanding Deep Learning with Keras,2nd Edition
by 作者: Matthew Moocarme,Mahla Abdolahnejad,Ritesh Bhagwat
pages 页数: 446 pages
Publisher Finelybook 出版社: Packt Publishing (February 28,2020)
Language 语言: English
ISBN-10 书号: 183921757X
ISBN-13 书号: 9781839217579
Book Description
Cut through the noise and get real results with a step-by-step approach to understanding deep learning with Keras programming
You already know that you want to learn Keras,and a smarter way to learn is to learn by 作者: doing. The Deep Learning with Keras Workshop focuses on building up your practical skills so that you can develop artificial intelligence applications or build machine learning models with Keras. You’ll learn from real examples that lead to real results.
Throughout The Deep Learning with Keras Workshop,you’ll take an engaging step-by-step approach to understand Keras. You won’t have to sit through any unnecessary theory. If you’re short on time you can jump into a single exercise each day or spend an entire weekend tinkering with your own neural networks. It’s your choice. Learning on your terms,you’ll build up and reinforce key skills in a way that feels rewarding.
Every physical print copy of The Deep Learning with Keras Workshop unlocks access to the interactive edition. With videos detailing all exercises and activities,you’ll always have a guided solution. You can also benchmark yourself against assessments,track progress,and receive content updates. You’ll even earn a secure credential that you can share and verify online upon completion. It’s a premium learning experience that’s included with your printed copy. To redeem,follow the instructions located at the start of your book.
Fast-paced and direct,The Deep Learning with Keras Workshop is the ideal companion for those who are just getting started with Keras. You’ll build and iterate on your code like a software developer,learning along the way. This process means that you’ll find that your new skills stick,embedded as best practice. A solid foundation for the years ahead.
What you will learn
Gain insight into the fundamental concepts of neural networks
Learn to think like a data scientist and understand the difference between machine learning and deep learning
Discover various techniques to evaluate,tweak,and improve your models
Explore different techniques to manipulate your data
Explore alternative techniques to verify the accuracy of your model
Contents
Preface
Chapter 1: Introduction to Machine Learning with Keras
Chapter 2: Machine Learning versus Deep Learning
Chapter 3: Deep Learning with Keras
Chapter 4: Evaluating Your Model with Cross-Validation Using Keras Wrappers
Chapter 5: Improving Model Accuracy
Chapter 6: Model Evaluation
Chapter 7: Computer Vision with Convolutional Neural Networks
Chapter 8: Transfer Learning and Pre-Trained Models
Chapter 9: Sequential Modeling with Recurrent Neural Networks
Appendix
Index
