Natural Language Processing in Action is a practical guide to processing and generating natural language text in the real world. In this book we provide you with all the tools and techniques you need to build the backend NLP systems to support a virtual assistant (chatbot), spam filter, forum moderator, sentiment analyzer, knowledge base builder, natural language text miner, or nearly any other NLP application you can imagine.
Natural Language Processing in Action is aimed at intermediate to advanced Python developers. Readers already capable of designing and building complex systems will also find most of this book useful, since it provides numerous best-practice examples and insight into the capabilities of state-of-the art NLP algorithms. While knowledge of object-oriented Python development may help you build better systems, it’s not required to use what you learn in this book. For special topics, we provide sufficient background material and cite resources (both text and online) for those who want to gain an in-depth understanding.
Natural Language Processing in action – Hobson Lane & Cole Howard & Hannes Max Hapke
Machine Learning with spark and python - Michael Bowles
Introduction to Deep Learning - Eugene Charniak
Building Chatbots with Python Using Natural Language Processing and Machine Learning - Sumit Raj
Artificial Intelligence - A Very Short Introduction - Margaret A.Boden
Deep Learning with Python - Francois Chollet
Artificial Intelligence - 101 things you must know today about our future - Lasse Rouhiainen
Deep Learning with Theano - Christopher Bourez
Deep Learning from Scratch - Building with Python form First Principles - Seth Weidman
Artificial Intelligence by example - Denis Rothman
Neural Networks - A visual introduction for beginners - Michael Taylor
Python for Programmers with introductory AI case studies - Paul Deitel & Harvey Deitel
Learning scikit-learn Machine Learning in Python - Raul Garreta & Guillermo Moncecchi
Python Data Analytics with Pandas, NumPy and Matplotlib - Fabio Nelli
Superintelligence - Paths, Danges, Strategies - Nick Bostrom
Generative Deep Learning - Teaching Machines to Paint, Write, Compose and Play - David Foster
Natural Language Processing Recipes - Akshay Kulkni & Adarsha Shivananda
Deep Learning with Applications Using Python - Navin Kumar Manaswi
Python Machine Learning - Sebastian Raschka
Practical computer vision applications using Deep Learning with CNNs - Ahmed Fawzy Gad
Deep Learning dummies second edition - John Paul Mueller & Luca Massaronf
Machine Learning - The art and science of alhorithms that make sense of data - Peter Flach
Machine Learning - A Probabilistic Perspective - Kevin P.Murphy
Introduction to the Math of Neural Networks - Jeff Heaton
Machine Learning with Python for everyone - Mark E.Fenner
Deep Learning with Python - Francois Cholletf
Deep Learning - Ian Goodfellow & Yoshua Bengio & Aaron Courville
The hundred-page Machine Learning Book - Andriy Burkov
Introducing Data Science - Davy Cielen & Arno D.B.Meysman & Mohamed Ali
TensorFlow for Deep Learning - Bharath Ramsundar & Reza Bosagh Zadeh
Intelligent Projects Using Python - Santanu Pattanayak
Python Machine Learning Second Edition - Sebastian Raschka & Vahid Mirjalili
Machine Learning Mastery with Python - Understand your data, create accurate models and work project...
