Welcome to this course: The Complete Natural Language Processing (NLP) Course. 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, and, in particular, concerned with programming computers to fruitfully process large natural language corpora. Natural Language Processing (NLP) is used in many applications to provide capabilities that were previously not possible. It involves analyzing text to obtain intent and meaning, which can then be used to support an application. This comprehensive course will get you up-and-running with advanced tasks using Natural Language Processing Techniques with Python.
The Data Mining Specialization teaches data mining techniques for both structured data which conform to a clearly defined schema, and unstructured data which exist in the form of natural language text. Specific course topics include pattern discovery, clustering, text retrieval, text mining and analytics, and data visualization. The Capstone project task is to solve real-world data mining challenges using a restaurant review data set from Yelp. You can apply to the degree program either before or after you begin the Specialization.
Get your team access to Udemy's top 3,000 courses anytime, anywhere. This course is designed to be accessible to brand new Python programmers but also worthwhile for more experienced Pythonistas who want to get started with AI and Natural Language processing. You do not any previous experience with Python or programming to be successful in this course. You can use a Windows or Mac computer to complete the course (or Linux for that matter).
Some 70 percent of companies claim they're using a form of artificial intelligence (A.I.), according to a new report by Constellation Research. That includes machine learning, deep learning, natural language processing, and cognitive computing. But while companies are interested in what A.I. can potentially do for them, many aren't willing to invest massive amounts of money in the endeavor. Some 92 percent of respondents reported overall A.I. budgets of less than $5 million, with 52 percent paying less than $1 million. However, most plan to increase their A.I.-related spending over the next year.