NLP books are natural language processing books. These books can supplement your NLP learning and give you a deep insight into the subject. Here are some of the top NLP books to read.
Practical Natural Language Processing: A Comprehensive Guide to Building Read-World NLP Systems
Published in the year 2020, this book outlines how one can build a real-world NLP system for your very own problem. It takes you through various steps needed for building a high-performance and efficient NLP setup customized as per your needs. The books covers various topics like different NLP tasks, different NLP and deep learning methods and also on how to fine-tune the models of your own setting. It teaches you evaluation of different approaches and also gives you an insight into software implementation and deployment.
Natural Language Processing with PyTorch: Build Intelligent Language Applications Using Deep Learning
This book is a practical guide that teaches you how to build NLP applications using the famous Pytorch library. This is a handy book that teaches you various computational graphs, supervised paradigm, basics of pytorch and traditional NLP methods. It also takes you to neural networks, word embeddings, sentence predictions and such other categories. This one is a good book for those who want to learn from practical examples and also use Pytorch for their development.
Deep Learning for Coders with Fastai and Pytorch: AI Applications without a PhD
This book demonstrates how deep learning is possible without availing a Phd degree in AI. It is a common misconception that has been cleared with this book. This book teaches you the popular framework and also aims the production and research of NLP into a little lines of the code. This book also teaches you how to build and train deep learning models and how to use the methods that are best to practice, improve accuracy and speed and also to deploy your model as a web application.
This is a great book on NLP that is very easy to understand. It focuses on the concepts behind neural network models that showcases how they are successful in solving the various problems. The beginning of this book covers various supervised learning modes, basics of working with text data, feedforward neural networks and computation-graph abstraction. The second half teaches you more specific model architectures that form the basis of any state-of-the art approaches recently such as CNN, RNN or LSTM.
This book is for advanced students of NLP, such as post-doctoral researchers or industry researchers who are looking for better guidance and knowledge. It is for those people who want to keep up their state-of-the-art in NLP education. This book reviews various methods such as speech recognition, dialogue systems, question answering, natural language generation, sentiment analysis and machine translation.
These are some of the best books on NLP learning. These best NLP books to read will definitely enhance your knowledge on the subject.