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After reading this book, you will be able to: - Understand the basics of deep learning, including its history, key concepts, and applications. - Explore the different types of deep learning architectures, such as convolutional neural networks and recurrent neural networks. - Learn how to train and optimize deep learning models. - Apply deep learning to real-world tasks, such as image classification and natural language processing. This book is intended for researchers and practitioners in the field of NLP who are interested in using deep learning and machine learning in their work. It will also be of interest to students who are taking courses on NLP or machine learning.This book will serve as an introduction to deep learning, and will cover various topics such as: - What is deep learning? - The history of deep learning - How deep learning works - Deep learning applications - The future of deep learning