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
Natural Language Processing Recipes - Akshay Kulkni & Adarsha Shivananda
Understanding Machine Learning from theory to algorithms - Shai Shalev-Shwartz & Shai Ben-David
Introduction to the Math of Neural Networks - Jeff Heaton
Python Machine Learning - Sebastian Raschka
Deep Learning with Applications Using Python - Navin Kumar Manaswi
Statistical Methods for Machine Learning - Disconver how to Transform data into Knowledge with Pytho...
TensorFlow for Deep Learning - Bharath Ramsundar & Reza Bosagh Zadeh
Neural Networks - A visual introduction for beginners - Michael Taylor
Machine Learning with spark and python - Michael Bowles
Neural Networks and Deep Learning - Charu C.Aggarwal
An introduction to neural networks - Kevin Gurney & University of Sheffield
Deep Learning with Python - Francois Cholletf
Intelligent Projects Using Python - Santanu Pattanayak
Python Data Structures and Algorithms - Benjamin Baka
Machine Learning - An Algorithmic Perspective second edition - Stephen Marsland
Artificial Intelligence - 101 things you must know today about our future - Lasse Rouhiainen
Artificial Intelligence by example - Denis Rothman
Amazon Machine Learning Developer Guild Version Latest
Applied Text Analysis with Python - Benjamin Benfort & Rebecca Bibro & Tony Ojeda
Python Machine Learning Cookbook - Practical solutions from preprocessing to Deep Learning - Chris A...
Natural Language Processing with Python - Steven Bird & Ewan Klein & Edward Loper
Deep Learning with Python - Francois Chollet
Deep Learning - Ian Goodfellow & Yoshua Bengio & Aaron Courville
Deep Learning with PyTorch - Vishnu Subramanian
Introduction to Scientific Programming with Python - Joakim Sundnes
Machine Learning - A Probabilistic Perspective - Kevin P.Murphy
Hands-On Machine Learning with Scikit-Learn and TensorFlow - Aurelien Geron
Deep Learning with Python - A Hands-on Introduction - Nikhil Ketkar
Machine Learning Applications Using Python - Cases studies form Healthcare, Retail, and Finance - Pu...
Python Deeper Insights into Machine Learning - Sebastian Raschka & David Julian & John Hearty
Medical Image Segmentation Using Artificial Neural Networks
Machine Learning - The art and science of alhorithms that make sense of data - Peter Flach
