Advanced_Deep_Learning_with_Keras.pdf

In recent years, deep learning has made unprecedented success stories in difficult problems in vision, speech, natural language processing and understanding, and all other areas with abundance of data. The interest in this field by companies, universities, governments, and research organizations has accelerated the advances in the field. This book covers select important advances in deep learning. The advanced theories are explained by giving a background of the principles, digging into the intuition behind the concepts, implementing the equations and algorithms using Keras, and examining the results. Artificial Intelligence (AI), as it stands today, is still far from being a well- understood field. Deep learning, as a sub field of AI, is in the same position. While it is far from being a mature field, many real-world applications such as vision-based detection and recognition, product recommendation, speech recognition and synthesis, energy conservation, drug discovery, finance, and marketing are already using deep learning algorithms. Many more applications will be discovered and built. The aim of this book is to explain advanced concepts, give sample implementations, and let the readers, as experts in their field, identify the target applications.