Deep Learning with TensorFlow and Keras - Third Edition

Build and deploy supervised, unsupervised, deep, and reinforcement learning models

Auteurs

• François Chollet
• Amita Kapoor
• Sujit Pal
• Antonio Gullì

Paramètres

• 698 pages
• 25 heures de lecture

En savoir plus sur le livre

Learn to build advanced machine and deep learning systems for various environments with this comprehensive guide. It covers neural networks and deep learning techniques using TensorFlow and Keras, focusing on writing applications within the powerful and scalable machine learning framework. The latest version, TensorFlow 2.x, emphasizes simplicity and user-friendliness, featuring updates like eager execution, intuitive APIs based on Keras, and flexible model building across platforms. The content provides an overview of supervised and unsupervised machine learning models, along with an in-depth analysis of deep learning and reinforcement learning through practical examples applicable to cloud, mobile, and large-scale production settings. The book details the creation of neural networks with TensorFlow and explores popular algorithms, including regression, convolutional neural networks (CNNs), transformers, generative adversarial networks (GANs), recurrent neural networks (RNNs), natural language processing (NLP), and graph neural networks (GNNs). Additionally, it includes working example applications and discusses TensorFlow in production, mobile, and AutoML contexts. Aimed at Python developers and data scientists, this hands-on resource equips readers with both the theoretical knowledge and practical skills necessary to develop machine learning systems using Keras, TensorFlow, and AutoML, with some prior machine learning k

Achat du livre

• Année de publication: 2022
• Reliure: (souple)