Deep learning with tensorflow and keras: build and deploy supervised, unsupervised,...
Описание
Build cutting edge machine and deep learning systems for the lab, production,
and mobile devices.
Key Features
Understand the fundamentals of deep learning and machine learning through
clear explanations and extensive code samples
Implement graph neural networks, transformers using Hugging Face and
TensorFlow Hub, and joint and contrastive learning
Learn cutting-edge machine and deep learning techniques
Book Description
Deep Learning with TensorFlow and Keras teaches you neural networks and deep
learning techniques using TensorFlow (TF) and Keras. You'll learn how to write
deep learning applications in the most powerful, popular, and scalable machine
learning stack available.
TensorFlow 2.x focuses on simplicity and ease of use, with updates like eager
execution, intuitive higher-level APIs based on Keras, and flexible model
building on any platform. This book uses the latest TF 2.0 features and
libraries to present an overview of supervised and unsupervised machine
learning models and provides a comprehensive analysis of deep learning and
reinforcement learning models using practical examples for the cloud, mobile,
and large production environments.
This book also shows you how to create neural networks with TensorFlow, runs
through popular algorithms (regression, convolutional neural networks (CNNs),
transformers, generative adversarial networks (GANs), recurrent neural
networks (RNNs), natural language processing (NLP), and graph neural networks
(GNNs)), covers working example apps, and then dives into TF in production, TF
mobile, and TensorFlow with AutoML.
What you will learn
Learn how to use the popular GNNs with TensorFlow to carry out graph mining
tasks
Discover the world of transformers, from pretraining to fine-tuning to
evaluating them
Apply self-supervised learning to natural language processing, computer
vision, and audio signal processing
Combine probabilistic and deep learning models using TensorFlow Probability
Train your models on the cloud and put TF to work in real environments
Build machine learning and deep learning systems with TensorFlow 2.x and the
Keras API
Who this book is for
This hands-on machine learning book is for Python developers and data
scientists who want to build machine learning and deep learning systems with
TensorFlow. This book gives you the theory and practice required to use Keras,
TensorFlow, and AutoML to build machine learning systems.
Some machine learning knowledge would be useful. We don't assume TF knowledge.
Table of Contents
Neural Networks Foundations with TF
Regression and Classification
Convolutional Neural Networks
Word Embeddings
Recurrent Neural Network
Transformers
Unsupervised Learning
Autoencoders
Generative Models
Self-Supervised Learning
Reinforcement Learning
Probabilistic TensorFlow
An Introduction to AutoML
The Math Behind Deep Learning
Tensor Processing Unit
Other Useful Deep Learning Libraries
Graph Neural Networks
Machine Learning Best Practices
TensorFlow 2 Ecosystem
Advanced Convolutional Neural Networks
Також купити книгу Deep Learning with TensorFlow and Keras: Build and deploy
supervised, unsupervised, deep, and reinforcement learning models, 3rd Edition
3rd ed. Edition, Amita Kapoor, Antonio Gulli, Sujit Pal, Francois Chollet,
more Ви можете по посиланню
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