Deep Learning in Practice helps you learn how to develop and optimize a model for your projects using Deep Learning (DL) methods and architectures. Key features: D emonstrates a quick review on Python, NumPy, and TensorFlow fundamentals. E xplains and provides examples of deploying TensorFlow and Keras in several projects. E xplains the fundamentals of Artificial Neural Networks (ANNs). P resents several examples and applications of ANNs. L earning the most popular DL algorithms features. E xplains and provides examples for the DL algorithms that are presented in this book. A nalyzes the DL network's parameter and hyperparameters. R eviews state-of-the-art DL examples. N ecessary and main steps for DL modeling. I mplements a Virtual Assistant Robot (VAR) using DL methods. N ecessary and fundamental information to choose a proper DL algorithm. G ives instructions to learn how to optimize your DL model IN PRACTICE . This book is useful for undergraduate and graduate students, as well as practitioners in industry and academia. It will serve as a useful reference for learning deep learning fundamentals and implementing a deep learning model for any project, step by step.