The Ultimate Beginners Guide to Natural Language Processing

The area of Natural Language Processing (NLP) is a subarea of Artificial Intelligence that aims to make computers capable of understanding human language, both written and spoken. Some examples of practical applications are: translators between languages, translation from text to speech or speech to text, chatbots, automatic question and answer systems (Q&A), automatic generation of descriptions for images, generation of subtitles in videos, classification of sentiments in sentences, among many others! Learning this area can be the key to bringing real solutions to present and future needs!

Based on that, this course was designed for those who want to grow or start a new career in Natural Language Processing, using the spaCy and NLTK (Natural Language Toolkit) libraries and the Python programming language! SpaCy was developed with the focus on use in production and real environments, so it is possible to create applications that process a lot of data. It can be used to extract information, understand natural language and even preprocess texts for later use in deep learning models.

The course is divided into three parts:

In the first one, you will learn the most basic natural language processing concepts, such as: part–of–speech, lemmatization, stemming, named entity recognition, stop words, dependency parsing, word and sentence similarity and tokenization