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
Deep Learning with Keras - Antonio Gulli & Sujit Pal
Python Deep Learning Cookbook - Indra den Bakker
Python 3 for Absolute Beginners - Tim Hall & J.P Stacey
Deep Learning from Scratch - Building with Python form First Principles - Seth Weidman
Natural Language Processing with Python - Steven Bird & Ewan Klein & Edward Loper
Python Deeper Insights into Machine Learning - Sebastian Raschka & David Julian & John Hearty
Deep Learning for Natural Language Processing - Palash Goyal & Sumit Pandey & Karan Jain
Python Deep Learning - Valentino Zocca & Gianmario Spacagna & Daniel Slater & Peter Roelants
Medical Image Segmentation Using Artificial Neural Networks
Python Machine Learning Eqution Reference - Sebastian Raschka
Python Data Structures and Algorithms - Benjamin Baka
Learning scikit-learn Machine Learning in Python - Raul Garreta & Guillermo Moncecchi
Python Data Analytics with Pandas, NumPy and Matplotlib - Fabio Nelli
Hands-On Machine Learning with Scikit-Learn and TensorFlow - Aurelien Geron
Statistical Methods for Machine Learning - Disconver how to Transform data into Knowledge with Pytho...
Deep Learning dummies first edition - John Paul Mueller & Luca Massaron
Neural Networks - A visual introduction for beginners - Michael Taylor
Introduction to Deep Learning - Eugene Charniak
Learn Keras for Deep Neural Networks - Jojo Moolayil
Python Machine Learning Second Edition - Sebastian Raschka & Vahid Mirjalili
Hands-on Machine Learning with Scikit-Learn, Keras & TensorFlow - Aurelien Geron
Python for Programmers with introductory AI case studies - Paul Deitel & Harvey Deitel
Introduction to Scientific Programming with Python - Joakim Sundnes
Deep Learning with Theano - Christopher Bourez
Fundamentals of Deep Learning - Nikhil Bubuma
Building Chatbots with Python Using Natural Language Processing and Machine Learning - Sumit Raj
The hundred-page Machine Learning Book - Andriy Burkov
R Deep Learning Essentials - Dr. Joshua F.Wiley
Pro Deep Learning with TensorFlow - Santunu Pattanayak
Scikit-learn Cookbook Second Edition over 80 recipes for machine learning - Julian Avila & Trent Hau...
Practical computer vision applications using Deep Learning with CNNs - Ahmed Fawzy Gad
Artificial Intelligence with an introduction to Machine Learning second edition - Richar E. Neapolit...
