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
Generative Deep Learning - Teaching Machines to Paint, Write, Compose and Play - David Foster
Machine Learning with spark and python - Michael Bowles
Intelligent Projects Using Python - Santanu Pattanayak
Python for Programmers with introductory AI case studies - Paul Deitel & Harvey Deitel
Python Machine Learning Eqution Reference - Sebastian Raschka
Deep Learning with Keras - Antonio Gulli & Sujit Pal
Introduction to Deep Learning - Eugene Charniak
Python Machine Learning Cookbook - Practical solutions from preprocessing to Deep Learning - Chris A...
Learn Keras for Deep Neural Networks - Jojo Moolayil
Understanding Machine Learning from theory to algorithms - Shai Shalev-Shwartz & Shai Ben-David
Neural Networks and Deep Learning - Charu C.Aggarwal
Natural Language Processing with Python - Steven Bird & Ewan Klein & Edward Loper
Machine Learning - A Probabilistic Perspective - Kevin P.Murphy
Python Data Analytics with Pandas, NumPy and Matplotlib - Fabio Nelli
Deep Learning with Applications Using Python - Navin Kumar Manaswi
Deep Learning with PyTorch - Vishnu Subramanian
Natural Language Processing Recipes - Akshay Kulkni & Adarsha Shivananda
Building Machine Learning Systems with Python - Willi Richert & Luis Pedro Coelho
Fundamentals of Deep Learning - Nikhil Bubuma
Deep Learning from Scratch - Building with Python form First Principles - Seth Weidman
Deep Learning - A Practitioner's Approach - Josh Patterson & Adam Gibson
Data Science and Big Data Analytics - EMC Education Services
Deep Learning with Python - A Hands-on Introduction - Nikhil Ketkar
Introducing Data Science - Davy Cielen & Arno D.B.Meysman & Mohamed Ali
Python 3 for Absolute Beginners - Tim Hall & J.P Stacey
TensorFlow for Deep Learning - Bharath Ramsundar & Reza Bosagh Zadeh
Python Machine Learning Third Edition - Sebastian Raschka & Vahid Mirjalili
Neural Networks - A visual introduction for beginners - Michael Taylor
An introduction to neural networks - Kevin Gurney & University of Sheffield
Medical Image Segmentation Using Artificial Neural Networks
Coding Theory - Algorithms, Architectures and Application
Deep Learning - Ian Goodfellow & Yoshua Bengio & Aaron Courville
