Natural Language Processing with Python Cookbook
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Natural Language Processing with Python Cookbook by Matthias Range
Learn the tricks and tips that will help you design Text Analytics solutions About This Book • Independent recipes that will teach you how to efficiently perform Natural Language Processing in Python • Use dictionaries to create your own named entities using this easy-to-follow guide • Learn how to implement NLTK for various scenarios with the help of example-rich recipes to take you beyond basic Natural Language Processing Who This Book Is For This book is intended for data scientists, data analysts, and data science professionals who want to upgrade their existing skills to implement advanced text analytics using NLP. Some basic knowledge of Natural Language Processing is recommended. What You Will Learn • Explore corpus management using internal and external corpora • Learn WordNet usage and a couple of simple application assignments using WordNet • Operate on raw text • Learn to perform tokenization, stemming, lemmatization, and spelling corrections, stop words removals, and more • Understand regular expressions for pattern matching • Learn to use and write your own POS taggers and grammars • Learn to evaluate your own trained models • Explore Deep Learning techniques in NLP • Generate Text from Nietzsche's writing using LSTM • Utilize the BABI dataset and LSTM to model episodes In Detail Natural Language Processing (NLP) is a field of computer science, artificial intelligence, and computational linguistics concerned with the interactions between computers and human (natural) languages; in particular, it's about programming computers to fruitfully process large natural language corpora. This book includes unique recipes that will teach you various aspects of performing Natural Language Processing with NLTK—the leading Python platform for the task. You will come across various recipes during the course, covering (among other topics) natural language understanding, Natural Language Processing, and syntactic analysis. You will learn how to understand language, plan sentences, and work around various ambiguities. You will learn how to efficiently use NLTK and implement text classification, identify parts of speech, tag words, and more. You will also learn how to analyze sentence structures and master lexical analysis, syntactic and semantic analysis, pragmatic analysis, and the application of deep learning techniques. By the end of this book, you will have all the knowledge you need to implement Natural Language Processing with Python. Style and Approach This book's rich collection of recipes will come in handy when you are working with Natural Language Processing with Python. Addressing your common and not-so-common pain points, this is a book that you must have on the shelf.
Krishna Bhavsar has spent around 10 years working on natural language processing, social media analytics, and text mining in various industry domains such as hospitality, banking, healthcare, and more. He has worked on many different NLP libraries such as Stanford CoreNLP, IBM's SystemText and BigInsights, GATE, and NLTK to solve industry problems related to textual analysis. He has also worked on analyzing social media responses for popular television shows and popular retail brands and products. He has also published a paper on sentiment analysis augmentation techniques in 2010 NAACL. he recently created an NLP pipeline/toolset and open sourced it for public use. Apart from academics and technology, Krishna has a passion for motorcycles and football. In his free time, he likes to travel and explore. He has gone on pan-India road trips on his motorcycle and backpacking trips across most of the countries in South East Asia and Europe. Naresh Kumar has more than a decade of professional experience in designing, implementing, and running very-large-scale Internet applications in Fortune Top 500 companies. He is a full-stack architect with hands-on experience in domains such as e-commerce, web hosting, healthcare, big data and analytics, data streaming, advertising, and databases. He believes in open source and contributes to it actively. Naresh keeps himself up-to-date with emerging technologies, from Linux systems internals to frontend technologies. He studied in BITS-Pilani, Rajasthan with dual degree in computer science and economics. Pratap Dangeti develops machine learning and deep learning solutions for structured, image, and text data at TCS, in its research and innovation lab in Bangalore. He has acquired a lot of experience in both analytics and data science. He received his master's degree from IIT Bombay in its industrial engineering and operations research program. Pratap is an artificial intelligence enthusiast. When not working, he likes to read about next-gen technologies and innovative methodologies. He is also the author of the book Statistics for Machine Learning by Packt.
| SKU | Nicht verfügbar |
| ISBN 13 | 9781787289321 |
| ISBN 10 | 178728932X |
| Titel | Natural Language Processing with Python Cookbook |
| Autor | Matthias Range |
| Buchzustand | Nicht verfügbar |
| Bindungsart | Paperback |
| Verlag | Packt Publishing Limited |
| Erscheinungsjahr | 2017-11-24 |
| Seitenanzahl | 316 |
| Hinweis auf dem Einband | Die Abbildung des Buches dient nur Illustrationszwecken, die tatsächliche Bindung, das Cover und die Auflage können sich davon unterscheiden. |
| Hinweis | Nicht verfügbar |