Hands-On Deep Learning Algorithms with Python
Hands-On Deep Learning Algorithms with Python:
Master deep learning algorithms with extensive math by implementing them using TensorFlow
by Sudharsan Ravichandiran
English | 2019 | ISBN: 1789344158 | 628 Pages | PDF EPUB MOBI (True) | 186 MB
Master deep learning algorithms with extensive math by implementing them using TensorFlow
by Sudharsan Ravichandiran
English | 2019 | ISBN: 1789344158 | 628 Pages | PDF EPUB MOBI (True) | 186 MB
This book introduces you to popular deep learning algorithms—from basic to advanced—and shows you how to implement them from scratch using TensorFlow. Throughout the book, you will gain insights into each algorithm, the mathematical principles behind it, and how to implement it in the best possible manner. The book starts by explaining how you can build your own neural networks, followed by introducing you to TensorFlow, the powerful Python-based library for machine learning and deep learning. Moving on, you will get up to speed with gradient descent variants, such as NAG, AMSGrad, AdaDelta, Adam, and Nadam. The book will then provide you with insights into RNNs and LSTM and how to generate song lyrics with RNN. Next, you will master the math for convolutional and capsule networks, widely used for image recognition tasks. Then you learn how machines understand the semantics of words and documents using CBOW, skip-gram, and PV-DM. Afterward, you will explore various GANs, including InfoGAN and LSGAN, and autoencoders, such as contractive autoencoders and VAE.