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***** BUY NOW (will soon return to 22.77 $) ***** Are you thinking of learning more Natural Language Processing (NLP) using TensorFlow? (For Beginners)This book is for you. It would seek to explain common terms and algorithms in an intuitive way. The authors used a progressive approach.This book and the accompanying examples, you would be well suited to tackle problems which pique your interests using NLP. From AI Sciences Publisher Our books may be the best one for beginners; it's a step-by-step guide for any person who wants to start learning Artificial Intelligence and Data Science from scratch. To get the most out of the concepts that would be covered, readers are advised to adopt a hands on approach which would lead to better mental representations. Target UsersThe book designed for a variety of target audiences. The most suitable users would include: Anyone who is intrigued by how algorithms arrive at predictions but has no previous knowledge of the field. Software developers and engineers with a strong programming background but seeking to break into the field of Data Science and NLP. Seasoned professionals in the field of artificial intelligence and machine learning who desire a bird's eye view of current techniques and approaches. What's Inside This Book? Introduction to Natural Language Processing What is Natural Language Processing Perspectivizing NLP: Areas of AI and Their Interdependencies Purpose of Natural Language Processing d104 Manipulation Tokenization Stemming Lemmatization Normalization Accessing d104 Corpora and Lexical Resources Processing Raw d104 Categorizing and Tagging Words NLP Applications d104 Classification Sentiment Classification Topic Modelling Question Answering Speech Recognition Machine Translation Word Representation Bag of Words One-Hot Encoding Word Vectors Representation Word2Vec and GloVe Learning to Classify d104 Supervised Classification Decision Trees Naive Bayes Classifiers Maximum Entropy Classifiers Deep Learning for NLP What is Deep Learning Feed Forward Neural Networks Recurrent Neural Networks Gated Recurrent Unit Long Short Term Memory Language Processing and Python using NLTK Introduction to TensorFlow d104 Classification Frequently Asked Questions Q: Does this book include everything I need to become a NLP expert?A: Unfortunately, no. This book is designed for readers taking their first steps in NLP and further learning will be required beyond this book to master all aspects of NLP. Q: Can I have a refund if this book doesn't fit for me?A: Yes, Amazon refund you if you aren't satisfied, for more information about the amazon refund service please go to the amazon help platform. ***** MONEY BACK GUARANTEE BY AMAZON ***** Editorial ReviewsMicheal Walker has a broad and deep knowledge of data science and Natural Language Processing. This book is an excellent introduction and helpful small book in Natural language processing. This is a great resource for quick and insightful tips for your NLP challenges. A. Perrier, Senior Strategy Consultant - Natural Language Processing, IBM You didn't need to have python and machine learning experience to get maximum benefit from this book. I would argue that even those with less Machine Learning experience can learn a lot from the book. This is a useful resource to have next to your computer in your day to day work. A. Thomas, Ph.D.

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