Natural Language Processing Projects

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Leverage machine learning and deep learning techniques to build fully-fledged natural language processing (NLP) projects. Projects throughout this book grow in complexity and showcase methodologies, optimizing tips, and tricks to solve various business problems. You will use modern Python libraries and algorithms to build end-to-end NLP projects. The book starts with an overview of NLP and artificial intelligence (AI) to provide a quick refresher of the algorithms. Next, it covers end-to-end NLP projects starting from traditional algorithms and projects such as customer review sentiment and emotion detection, topic modeling, and document clustering. Then, it delves into ecommerce projects such as product categorization using the description of the product, a search engine to retrieve the relevant content, and a content-based recommendation system to enhance user experience. The book explains how to build systems to find similar sentences using contextual embedding, résumé parsing and shortlisting, summarizing huge documents using RNN, automatic word suggestion using LSTM, and building a chatbot using transfer learning. The book concludes with a discussion of next-generation AI and algorithms which are in the research space. By the end of this book, you will be able to solve various business problems using NLP techniques. What You Will LearnImplement full-fledged intelligent NLP applications with PythonTranslate real-world business problems on text data with NLP techniquesUse machine learning and deep learning techniques to perform smart language processingProvides hands-on experience and end-to-end implementation of search engines: information retrieval, text summarization, chatbots, text generation, document clustering, product classification, and more Who This Book Is For Data scientists, machine learning engineers, and deep learning professionals looking to build natural language applications using Python