The latest advances in deep learning are enabling applications that recognize text and speech with exceptional accuracy. What is the result? Chatbots are appearing that conduct dialogue no worse than real people, programs that effectively select resumes for a given vacancy, excellent predictive search is being developed, and document annotations are automatically generated. Thanks to new techniques and tools like Keras and Tensorflow, it's easier than ever to implement good natural language processing (NLP).

Natural Language Processing in Action is your guide to creating programs that can recognize and interpret human language. The publication describes how, using ready-made packages in the Python language, extract meanings from text and adequately manage them. The book provides an expanded interpretation of traditional NLP methods, which will allow the use of neural networks, modern deep learning algorithms and generative techniques in solving real-life problems, such as identifying dates and names, composing texts and answering unexpected questions.