Learn about Python Natural Language Processing (NLP) in 2 Hours

In this video we are going to learn about Python Natural Language Processing (NLP) in 2 Hours. there are different topics that we are going to cover in this video like tokenization, stemming, lemmatization, parts of speech tagging, named entity recognition, sentiment analysis, language translation and many more. Python Natural Language Processing (NLP) in 2 Hours

In this video we are going to learn about Python Natural Language Processing (NLP) in 2 Hours. there are different topics that we are going to cover in this video like tokenization, stemming, lemmatization, parts of speech tagging, named entity recognition, sentiment analysis, language translation and many more.

What Python Natural Language Processing (NLP) ?

Natural Language Processing (NLP) is concerned with the interaction between natural language and the computer. It is one of the major components of Artificial Intelligence (AI) and computational linguistics.

Natural language processing is used everywhere, from search engines such as Google , to voice interfaces such as Siri, and there are different other usages of nlp like spell checking, spam filtering, related keyword in search engines, knowledge base support , chat bots., machine translation, speech recognition and many more.

What is NLTK ?

NLTK is also a very good learning kit because the learning curve of Python (on which NLTK is written) is very fast. NLTK has incorporated most of the NLP tasks, it' is very elegant and easy to work with. For all these reasons, NLTK has become one of the most libraries in the NLP community.

What TextBlob ?

TextBlob is a Python (2 and 3) library for processing textual data. It provides a simple API for diving into common natural language processing (NLP) tasks such as part-of-speech tagging, noun phrase extraction, sentiment analysis, classification, translation, and more.

nlp natural language processing python

Natural language processing (NLP) is a specialized field for analysis and generation of human languages. Human languages, rightly called natural language, are highly context-sensitive and often ambiguous in order to produce a distinct meaning. (Remember the joke where the wife asks the husband to "get a carton of milk and if they have eggs, get six," so he gets six cartons of milk because they had eggs.) NLP provides the ability to comprehend natural language input and produce natural language output appropriately.

Teaching machines to understand human context can be a daunting task. With the current evolving landscape, Natural Language Processing (NLP) has turned out to be an extraordinary breakthrough with its advancements in semantic and linguistic knowledge.NLP is vastly leveraged by businesses to build customised chatbots and voice assistants using its optical character and speed recognition

Tools and techniques to accelerate your Python NLP projects. Natural Language Processing (NLP): Don't Reinvent the Wheel. Tools and techniques to accelerate your Python NLP projects.

Tutorial on the basics of natural language processing (NLP) with sample coding implementations in Python. We dive into the natural language toolkit (NLTK) library to present how it can be useful for natural language processing related-tasks. Afterward, we will discuss the basics of other Natural Language Processing libraries and other essential methods for NLP, along with their respective coding sample implementations in Python.

Tutorial on the basics of natural language processing (NLP) with sample coding implementations in Python. In this article, we explore the basics of natural language processing (NLP) with code examples. We dive into the natural language toolkit (NLTK) library to present how it can be useful for natural language processing related-tasks. Afterward, we will discuss the basics of other Natural Language Processing libraries and other essential methods for NLP, along with their respective coding sample implementations in Python.