Natural Language Processing Recipes is your handy problem-solution reference for learning and implementing NLP solutions using Python. The
book is packed with thousands of code and approaches that help you to quickly learn and implement the basic and advanced Natural Language
Processing techniques. You will learn how to efficiently use a wide range of NLP packages and implement text classification, identify parts of speech,
topic modeling, text summarization, text generation, sentiment analysis, and many more applications of NLP.
This book starts off by ways of extracting text data along with web scraping. You will also learn how to clean and preprocess text data and ways to analyze them with advanced algorithms. During the course of the book, you will explore the semantic as well as syntactic analysis of the text. We will be covering complex NLP solutions that will involve text normalization, various advanced preprocessing methods, POS tagging, text similarity, text summarization, sentiment analysis, topic modeling, NER, word2vec, seq2seq, and much more. In this book, we will cover the various fundamentals necessary for applications of machine learning and deep learning in natural language processing, and the other state-of-the-art techniques. Finally, we close it with some of the advanced industrial applications of NLP with the solution approach and implementation, also leveraging the power of deep learning techniques for Natural Language Processing and Natural Language Generation problems. Employing state-of-the-art advanced RNNs, like long short-term memory, to solve complex text generation tasks. Also, we explore word embeddings. Each chapter includes several code examples and illustrations.
By the end of the book, the reader will have a clear understanding of implementing natural language processing and will have worked on
multiple examples that implement NLP techniques in the real world. The reader will be comfortable with various NLP techniques coupled with machine learning and deep learning and its industrial applications, which make the NLP journey much more interesting and will definitely help improve Python coding skills as well. You will learn about all the ingredients that you need to, to become successful in the NLP space.
