Python for Natural Language Processing (NLP)

Learn Natural Language Processing (NLP) and its Python Implementation. Build NLP models.

Welcome to the landing page of Python for Natural Language Processing (NLP) course. This course is built for students who want to learn NLP concepts in Python. Course starts with the repeat of the Python Fundamentals. After it text methods and pandas library is covered in the course. Text methods will be helpful when we are going to be building Natural Language Processing projects. We will use pandas library for reading and analyzing our data sets. After it we will cover some fatures of spaCy library like part of speech tagging, tokenization and named entity recognition. spaCy with NLTK are the both most popular Python libraries for Natural Language Processing.  After covering that concepts we will move into evaluation of model performances section and there we will be learning how the NLP models will be evaluated. After that task we will see Sentiment Analysis and Text Classification and we will make examples of them. At the final lectures of the course we will build a Natural Language Processing project from stratch with what we learned through the course and we will finish. At the whole course process and after it, students can reach to me about the course concepts via Q&A section of the course or direct messages on Udemy. Thanks for visiting course page and reading course description.

Python for Natural Language Processing (NLP)

Learn Natural Language Processing (NLP) and its Python Implementation. Build NLP models.»

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