Principles and Labs for Deep Learning 5th Edition Shih-Chia Huang

Principles and Labs for Deep Learning – Ebook Instant Download/Delivery ISBN(s): 9780323901994,0323901999

Product details:

• ISBN-10 ‏ : ‎ 0323901999
• ISBN-13 ‏ : ‎ 9780323901994
• Author: Dr. Shih-Chia Huang

Principles and Labs for Deep Learning provides the knowledge and techniques needed to help readers design and develop deep learning models. Deep Learning techniques are introduced through theory, comprehensively illustrated, explained through the TensorFlow source code examples, and analyzed through the visualization of results. The structured methods and labs provided by Dr. Huang and Dr. Le enable readers to become proficient in TensorFlow to build deep Convolutional Neural Networks (CNNs) through custom APIs, high-level Keras APIs, Keras Applications, and TensorFlow Hub.  Each chapter has one corresponding Lab with step-by-step instruction to help the reader practice and accomplish a specific learning outcome.

Deep Learning has been successfully applied in diverse fields such as computer vision, audio processing, robotics, natural language processing, bioinformatics and chemistry. Because of the huge scope of knowledge in Deep Learning, a lot of time is required to understand and deploy useful, working applications, hence the importance of this new resource. Both theory lessons and experiments are included in each chapter to introduce the techniques and provide source code examples to practice using them. All Labs for this book are placed on GitHub to facilitate the download. The book is written based on the assumption that the reader knows basic Python for programming and basic Machine Learning.

Table contents:

Chapter 1: Introduction to TensorFlow

Chapter 2: Regression Problem

Chapter 3: Binary classification problem

Chapter 4: Multi-category Classification Problem

Chapter 5: Training Neural Network

Chapter 6: Advanced TensorFlow

Chapter 7: Advanced TensorBoard

Chapter 8: Convolutional Neural Network Architectures

Chapter 9: Transfer Learning

Chapter 10: Variational Auto-Encoder

Chapter 11: WGAN-GP

People also search:

deep learning requirements

deep learning formula

deep learning learning rate

the principles of deep learning

the principles of deep learning theory

the principles of deep learning theory pdf