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Case Natural Language Processing:Concept along with Study

Case Natural Language Processing:Concept along with Study Free Course: Natural Language Processing (NLP), Text Processing, Machine Learning, Spam Filter

  • What are various text processing techniques and their implementation in python.
  • Case Study: Role of Hashing in Spam Filter compared to Countvectorizer.

Requirements

  • Basic Understanding of Python
  • One Laptop with Python IDE installed
  • Understanding of Machine learning will be helpful in Case Study however not mandatory

Description

This course provides a basic understanding of NLP. Anyone can opt for this course. No prior understanding of NLP is required.  Text Processing like Tokenization, Stop Words Removal, Stemming, different types of Vectorizers, WSD, etc are explained in detail with python code. Also difference between CountVectorizer and Hashing in Spam Filter.

Who this course is for:

  • People willing to learn NLP and looking forward to build career in Machine Learning.

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