Python-based Machine Learning and Deep Learning for Natural Language Processing
NLP is an interdisciplinary topic that integrates computer science, artificial intelligence, and linguistics to create algorithms and models that can process and interpret human language. The purpose of natural language processing (NLP) is to allow computers to comprehend, interpret, and produce human language, which includes speech and text. Chatbots for customer service, sentiment analysis for marketing and social media, named entity recognition for information extraction, machine translation for multilingual communication, and speech recognition for handsfree contact with technology are just a few examples. Advances in machine learning, deep learning, and big data have fueled the development of NLP approaches, which continue to improve to meet the demands of new applications. Python is one of the most popular programming languages for natural language processing (NLP) because of its ease of use, readability, and the availability of strong libraries and tools such as NLTK, spaCy, and Gensim. 1.1 OVERVIEW Natural Language Processing (NLP) is a branch of computer science, artificial intelligence, and computational linguistics dealing with computer-human interaction. NLP's purpose is to enable computers to analyse, comprehend, and produce human language, which includes speech and text. This has resulted in a wide range of applications in various industries, including customer service chatbots, sentiment analysis for marketing and social media, named entity recognition for information extraction, machine translation for multilingual communication, and speech recognition for hands-free technology interaction