Hands-On Natural Language Processing with Python (e-book)

Hands-On Natural Language Processing with Python (e-book) - Opis

Natural language processing (NLP) has found its application in various domains, such as web search, advertisements, and customer services, and with the help of deep learning, we can enhance its performances in these areas. Hands-On Natural Language Processing with Python teaches you how to leverage deep learning models for performing various NLP tasks, along with best practices in dealing with today’s NLP challenges.To begin with, you will understand the core concepts of NLP and deep learning, such as Convolutional Neural Networks (CNNs), recurrent neural networks (RNNs), semantic embedding, Word2vec, and more. You will learn how to perform each and every task of NLP using neural networks, in which you will train and deploy neural networks in your NLP applications. You will get accustomed to using RNNs and CNNs in various application areas, such as text classification and sequence labeling, which are essential in the application of sentiment analysis, customer service chatbots, and anomaly detection. You will be equipped with practical knowledge in order 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 versed in building deep learning-backed NLP applications, along with overcoming NLP challenges with best practices developed by domain experts. Spis treści: 1. Getting Started2. Text Classification and POS Tagging Using NLTK3. Deep Learning and TensorFlow4. Semantic Embedding Using Shallow Models5. Text Classification Using LSTM6. Searching and DeDuplicating Using (...) więcej CNNs7. Named Entity Recognition Using Character LSTM8. Text Generation and Summarization Using GRUs9. Question-Answering and Chatbots Using Memory Networks10. Machine Translation Using the Attention-Based Model11. Speech Recognition Using DeepSpeech12. Text-to-Speech Using Tacotron13. Deploying Trained Models mniej