Category Review: Natural Language Processing with Python Cookbook Natural language processing (NLP) is a field of artificial intelligence that deals with the interaction between computers and humans using natural language. It involves tasks such as text classification, sentiment analysis, named entity recognition, and machine translation. NLP has many applications in areas such as customer service, healthcare, finance, and e-commerce. The Natural Language Processing with Python Cookbook is a great resource for anyone interested in learning how to implement text analytics solutions using deep learning principles and Python. The book contains over 60 recipes that cover various NLP tasks such as tokenization, stemming, lemmatization, part-of-speech tagging, named entity recognition, sentiment analysis, topic modeling, and more. One of the strengths of this book is its practical approach to learning NLP with Python. The author provides clear explanations and examples for each recipe, making it easy for beginners to understand the concepts and implement them in their own projects. Additionally, the book includes code snippets and sample datasets that readers can use to experiment with the recipes and test their understanding of the material. Another advantage of this book is its focus on deep learning principles. Deep learning has become increasingly popular in recent years for NLP tasks such as sentiment analysis and machine translation. The author provides a thorough introduction to deep learning concepts such as neural networks, convolutional neural networks (CNNs), recurrent neural networks (RNNs), and long short-term memory (LSTM) networks. Readers will learn how to implement these models using Python libraries such as TensorFlow and Keras. Overall, the Natural Language Processing with Python Cookbook is a great resource for anyone interested in learning NLP with Python. The book provides a practical approach to learning NLP concepts and implementing them using deep learning principles.