TensorFlow in Action

Fundamentals of TensorFlow
Implementing deep learning networks
Picking a high-level Keras API for model building with confidence
Writing comprehensive end-to-end data pipelines
Building models for computer vision and natural language processing
Utilizing pretrained NLP models
Recent algorithms including transformers, attention models, and ElMoIn TensorFlow in Action, you’ll dig into the newest version of Google’s amazing TensorFlow framework as you learn to create incredible deep learning applications. Author Thushan Ganegedara uses quirky stories, practical examples, and behind-the-scenes explanations to demystify concepts otherwise trapped in dense academic papers. As you dive into modern deep learning techniques like transformer and attention models, you’ll benefit from the unique insights of a top StackOverflow contributor for deep learning and NLP.Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.

Google’s TensorFlow framework sits at the heart of modern deep learning. Boasting practical features like multi-GPU support, network data visualization, and easy production pipelines using TensorFlow Extended (TFX), TensorFlow provides the most efficient path to professional AI applications. And the Keras library, fully integrated into TensorFlow 2, makes it a snap to build and train even complex models for vision, language, and more.