The goal of this task is to predict a class (label) of a document, or rank documents within in a list based on their relevance. It could be used in spam filtering (predicting whether an e-mail is spam or not) or content classification (selecting articles from the web about what is happening to your competitors). Sentiment analysis aims to determine the attitude or emotional reaction of a person with respect to some topic- e.g.,positive or negative attitude, anger, sarcasm. It is broadly used in customer satisfaction studies (e.g. Document Summarization is a set of methods for creating short, meaningful descriptions of long texts (i.e.
Welcome to the best Natural Language Processing course on the internet! This course is designed to be your complete online resource for learning how to use Natural Language Processing with the Python programming language. In the course we will cover everything you need to learn in order to become a world class practitioner of NLP with Python. We'll start off with the basics, learning how to open and work with text and PDF files with Python, as well as learning how to use regular expressions to search for custom patterns inside of text files. Afterwards we will begin with the basics of Natural Language Processing, utilizing the Natural Language Toolkit library for Python, as well as the state of the art Spacy library for ultra fast tokenization, parsing, entity recognition, and lemmatization of text.
Most humans are pretty good at reading and interpreting text; computers...not so much. Natural Language Processing (NLP) is the discipline of teaching computers to read more like people, and you see examples of it in everything from chatbots to the speech-recognition software on your phone. Modern NLP techniques based on machine learning radically improve the ability of software to recognize patterns, use context to infer meaning, and accurately discern intent from poorly-structured text. NLP promises to help you improve customer interactions, save cost, and reinvent text-intensive applications like search or product support.
The field of artificial intelligence (AI) is comprised of many disciplines, technologies and subfields. There are dozens of terms that are used to describe AI technologies, and the definitions can be complex and confusing. A large part of our focus with the Marketing AI Institute is to make AI more approachable and actionable. To do that, we've created this AI terms cheat sheet, which features easy, accessible definitions of core AI terminology. We encourage you to skip to the term you're curious about.