Build machine and deep learning systems with TensorFlow 2 and Keras for lab, production, and mobile devices. This resource introduces TensorFlow 2 and Keras from the outset, teaching essential machine and deep learning techniques through clear explanations and extensive code samples. The second edition focuses on neural networks and deep learning alongside TensorFlow and Keras, enabling the creation of deep learning applications using a powerful and scalable machine learning stack. TensorFlow is the preferred library for professional applications, while Keras provides a user-friendly Python API for TensorFlow access. The book covers various applications, including regression, convolutional networks (CNNs), generative adversarial networks (GANs), recurrent neural networks (RNNs), and natural language processing (NLP). It includes two practical example apps and discusses deploying TensorFlow in production and mobile environments, as well as utilizing AutoML. Readers will learn to build machine learning systems, apply regression analysis, understand CNNs for image classification, generate new data with GANs, process sequences with RNNs, and automate ML workflows using Google tools. This book is ideal for Python developers and data scientists looking to enhance their machine learning and deep learning expertise with TensorFlow and Keras, assuming some prior knowledge of the field.
