Hands-on Natural Language Processing with Python: Uncover deep learning models, best practices and bring the human capabilities into your applications

Foster your NLP applications with capabilities of deep learning, NLTK and TensorFlowKey FeaturesPerform NLP tasks and train NLP models using NLTK and powerful TensorFlowBoost your NLP models with strong deep learning architectures like CNNs and RNNsGain practical skills in implementing neural networks into your linguistic applications across mobile and cloud platformsBook DescriptionNatural Language Processing (NLP) has found its applications in various domains like web search, advertisements, customer service and with Deep Learning, we can bring high performance in these application areas. This book teaches you to leverage deep learning models in performing various NLP tasks; it also showcases the best practices in dealing with the NLP challenges.To start with, we will explain the core concepts of NLP and Deep Learning such as CNN, RNN, Semantic Embedding, Information Extraction, word2vec and so on. Then the book will focus on the applications of the neural network with respect to the tasks of NLP. You will learn to perform each task of NLP using a neural network and how to use LSTM, CNN for text classification, sequence labeling and so on which are essential in the application of sentiment analysis, customer service chatbot and anomaly detection.. You will be equipped with the practical knowledge to implement deep learning in your linguistic applications using Python's popular deep learning library, TensorFlow.By the end of this book, you will be well trained in building deep learning backed NLP applications along with overcoming the NLP challenges with some of the best practices developed by domain experts.What you will learnImplement semantic embedding of words to classify and find entitiesConvert word to vectors by training to implement arithmetic on words Train a deep learning model to detect classification of tweets, newsImplement a question-answering model with search and RNN modelsTrain models for various text classification datasets using CNNTrain a model to convert speech to text using DeepSpeechImplement wave net for natural sounding voice, a deep generative modelLearn how to convert to voice to text and text to voice in a natural wayWho This Book Is ForIf you are a developer and want to build a deep learning application that leverages Natural Language Processing (NLP) techniques. All you need is the basics of machine learning and Python to decode the entire book.

Author: Rajalingappaa Shanmugmani

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