Natural Language Processing in action – Hobson Lane & Cole Howard & Hannes Max Hapke

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.

Related posts:

Deep Learning with Keras - Antonio Gulli & Sujit Pal
Natural Language Processing with Python - Steven Bird & Ewan Klein & Edward Loper
Python Deep Learning - Valentino Zocca & Gianmario Spacagna & Daniel Slater & Peter Roelants
Learning scikit-learn Machine Learning in Python - Raul Garreta & Guillermo Moncecchi
Practical computer vision applications using Deep Learning with CNNs - Ahmed Fawzy Gad
Deep Learning for Natural Language Processing - Jason Brownlee
Deep Learning Illustrated - A visual, Interactive Guide to Arficial Intelligence First Edition - Jon...
Deep Learning for Natural Language Processing - Palash Goyal & Sumit Pandey & Karan Jain
Deep Learning with Python - Francois Chollet
Machine Learning - A Probabilistic Perspective - Kevin P.Murphy
Deep Learning with Hadoop - Dipayan Dev
Introduction to Machine Learning with Python - Andreas C.Muller & Sarah Guido
Pattern recognition and machine learning - Christopher M.Bishop
Introduction to Deep Learning Business Application for Developers - Armando Vieira & Bernardete Ribe...
Artificial Intelligence - 101 things you must know today about our future - Lasse Rouhiainen
Machine Learning Applications Using Python - Cases studies form Healthcare, Retail, and Finance - Pu...
Foundations of Machine Learning second edition - Mehryar Mohri & Afshin Rostamizadeh & Ameet Talwalk...
Medical Image Segmentation Using Artificial Neural Networks
Scikit-learn Cookbook Second Edition over 80 recipes for machine learning - Julian Avila & Trent Hau...
Introducing Data Science - Davy Cielen & Arno D.B.Meysman & Mohamed Ali
Hands-On Machine Learning with Scikit-Learn and TensorFlow - Aurelien Geron
Introduction to Deep Learning - Eugene Charniak
Python Data Analytics with Pandas, NumPy and Matplotlib - Fabio Nelli
Python Machine Learning Third Edition - Sebastian Raschka & Vahid Mirjalili
Building Machine Learning Systems with Python - Willi Richert & Luis Pedro Coelho
Hands-on Machine Learning with Scikit-Learn, Keras & TensorFlow - Aurelien Geron
Statistical Methods for Machine Learning - Disconver how to Transform data into Knowledge with Pytho...
Applied Text Analysis with Python - Benjamin Benfort & Rebecca Bibro & Tony Ojeda
Python Deeper Insights into Machine Learning - Sebastian Raschka & David Julian & John Hearty
Python Machine Learning - Sebastian Raschka
Intelligent Projects Using Python - Santanu Pattanayak
The hundred-page Machine Learning Book - Andriy Burkov