کتاب کارگاه آموزشی عمیق: مهارت های لازم برای توسعه مدل های یادگیری عمیق نسل بعدی خود را با Tensorflow و Keras بیاموزید

Take a hands-on approach to understanding deep learning and build smart applications that can recognize images and interpret text
Key Features

Understand how to implement deep learning with TensorFlow and Keras
Learn the fundamentals of computer vision and image recognition
Study the architecture of different neural networks

Book Description

Are you fascinated by how deep learning powers intelligent applications such as self-driving cars, virtual assistants, facial recognition devices, and chatbots to process data and solve complex problems? Whether you are familiar with machine learning or are new to this domain, The Deep Learning Workshop will make it easy for you to understand deep learning with the help of interesting examples and exercises throughout.

The book starts by highlighting the relationship between deep learning, machine learning, and artificial intelligence and helps you get comfortable with the TensorFlow 2.0 programming structure using hands-on exercises. You’ll understand neural networks, the structure of a perceptron, and how to use TensorFlow to create and train models. The book will then let you explore the fundamentals of computer vision by performing image recognition exercises with convolutional neural networks (CNNs) using Keras. As you advance, you’ll be able to make your model more powerful by implementing text embedding and sequencing the data using popular deep learning solutions. Finally, you’ll get to grips with bidirectional recurrent neural networks (RNNs) and build generative adversarial networks (GANs) for image synthesis.

By the end of this deep learning book, you’ll have learned the skills essential for building deep learning models with TensorFlow and Keras.
What you will learn

Understand how deep learning, machine learning, and artificial intelligence are different
Develop multilayer deep neural networks with TensorFlow
Implement deep neural networks for multiclass classification using Keras
Train CNN models for image recognition
Handle sequence data and use it in conjunction with RNNs
Build a GAN to generate high-quality synthesized images

Who this book is for

If you are interested in machine learning and want to create and train deep learning models using TensorFlow and Keras, this workshop is for you. A solid understanding of Python and its packages, along with basic machine learning concepts, will help you to learn the topics quickly.
Table of Contents

Building Blocks of Deep Learning
Neural Networks
Image Classification with Convolutional Neural Networks (CNNs)
Deep Learning for Text – Embeddings
Deep Learning for Sequences
LSTMs, GRUs, and Advanced RNNs
Generative Adversarial Networks