Unlock the TensorFlow design secrets behind successful deep learning applications Deep learning StackOverflow contributor Thushan Ganegedara teaches you the new features of TensorFlow 2 in this hands-on guide.In TensorFlow in Action you will learn: nbspnbspnbsp Fundamentals of TensorFlow nbspnbspnbsp Implementing deep learning networks nbspnbspnbsp Picking a high-level Keras API for model building with confidence nbspnbspnbsp Writing comprehensive end-to-end data pipelines nbspnbspnbsp Building models for computer vision and natural language processing nbspnbspnbsp Utilizing pretrained NLP models nbspnbspnbsp Recent algorithms including transformers, attention models, and ElMo  In 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, you8217ll 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.  About the technology Google8217s 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.  About the book TensorFlow in Action teaches you to construct, train, and deploy deep learning models using TensorFlow 2. In this practical tutorial, you8217ll build reusable skill hands-on as you create production-ready applications such as a French-to-English translator and a neural network that can write fiction. You8217ll appreciate the in-depth explanations that go from DL basics to advanced applications in NLP, image processing, and MLOps, complete with important details that you8217ll return to reference over and over.  What's inside nbspnbspnbsp Covers TensorFlow 2.9 nbspnbspnbsp Recent algorithms including transformers, attention models, and ElMo nbspnbspnbsp Build on pretrained models nbspnbspnbsp Writing end-to-end data pipelines with TFX About the reader For Python programmers with basic deep learning skills.  About the author Thushan Ganegedara is a senior ML engineer at Canva and TensorFlow expert. He holds a PhD in machine learning from the University of Sydney. Table of Contents PART 1 FOUNDATIONS OF TENSORFLOW 2 AND DEEP LEARNING 1 The amazing world of TensorFlow 2 TensorFlow 2 3 Keras and data retrieval in TensorFlow 2 4 Dipping toes in deep learning 5 State-of-the-art in deep learning: Transformers PART 2 LOOK MA, NO HANDS DEEP NETWORKS IN THE REAL WORLD 6 Teaching machines to see: Image classification with CNNs 7 Teaching machines to see better: Improving CNNs and making them confess 8 Telling things apart: Image segmentation 9 Natural language processing with TensorFlow: Sentiment analysis 10 Natural language processing with TensorFlow: Language modeling PART 3 ADVANCED DEEP NETWORKS FOR COMPLEX PROBLEMS 11 Sequence-to-sequence learning: Part 1 12 Sequence-to-sequence learning: Part 2 13 Transformers 14 TensorBoard: Big brother of TensorFlow 15 TFX: MLOps and deploying models with TensorFlow