finelybook
The Deep Learning Workshop: Learn the skills you need to develop your own next-generation deep learning models with TensorFlow and Keras: Take a ... that can recognize images and interpret text
31 July 2020
by 作者: Mirza Rahim Baig ,Thomas V. Joseph ,Nipun Sadvilkar ,Mohan Kumar Silaparasetty ,Anthony So pages 页数: 474 pages
ISBN-13 书号: 9781839219856
ISBN-10 书号: 1839219858
05 x 2.72 x 23.5 cm
Publisher Finelybook 出版社: Packt Publishing (31 July 2020)
Language 语言: English
Book Description
Take a hands-on approach to understanding deep learning and build smart applications that can recognize images and interpret text
Are you fascinated by 作者: 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 作者: 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 作者: 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 作者: 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
