Название: Deep Learning with TensorFlow and KerasАвтор: Pratap Dangeti
Издательство: Wiley
Год: 2020
Страниц: 339
Язык: английский
Формат: epub
Размер: 11.8 MB
Truly a must have guide for every Data Science professional and deep learning enthusiast, the Wiley Deep Learning with Keras and TensorFlow brings together industry best practices, detailed code descriptions with simplified explanations and solved real life problems, to help any beginner to learn and master the techniques of Deep learning and coding in Keras and TensorFlow.
Deep Learning is a fascinating subject. While it helps solve advance Artificial Intelligence (AI) problems, it also worries a lot of new entrants in this field due to the complex black box nature of the models and the need for deep mathematical understanding as pre-requisite. Before building customized Deep Learning models to solve specific requirement—be it vision, text or speech—one should understand the various fundamentals and knobs of the models so that they can tune for the best possible combinations.
In this book, care has been taken not to overwhelm the reader with complex mathematics and unnecessary equations. Instead, it simplifies the fundamentals with enough reasoning, thus making it easy for comprehension.
The book covers the basic building blocks of Deep Learning and its implementation in Python from scratch to solve advance problems using both TensorFlow and Keras software. TensorFlow has been chosen to help developers implement models in production environments and Keras for quickly prototyping new ideas in research scenarios. The book also includes best practices to improve the effectiveness in terms of tuning the models, handling memory constraints and usage of logs to save intermediate outputs. Finally, it concludes with the introduction to deep reinforcement learning for solving advanced problems in the field of AI and Artificial General Intelligence.
The entire book has been divided into nine chapters to cover the breadth and depth of Deep Learning:
Chapter 1: Fundamentals of Artificial Intelligence and Deep Learning
Chapter 2: Parallel Processing and Graphics Processing Unit (GPU) Fundamentals
Chapter 3: Getting Started with TensorFlow
Chapter 4: Getting Started with Keras
Chapter 5: Structured Data Processing with Deep Learning Models
Chapter 6: Image Processing with Deep Learning
Chapter 7: Natural Language Processing and Text Analysis with Deep Learning
Chapter 8: Unsupervised Learning and Generative Adversarial Networks with Deep Learning
Chapter 9: Best Practices in Deep Learning and Introduction of Deep Reinforcement Learning
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