Natural Language Processing:Concept along with Case Study
- Basic Understanding of Python
- One Laptop with Python IDE installed
- Understanding of Machine learning will be helpful in Case Study however not mandatory
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.
- 04:49What is Natural Language Processing (NLP)
- 03:28Stop Words Removal
- 02:04Word Sense Disambiguation
- 05:34Count Vectorizer
- 07:30TF-IDF Vectorizer
- 04:21Hashing Vectorizer
A total of 13 years of experience. I started my career as a programmer. Apart from programming, I have worked on Cloud & Virtualization technology, DevOps and Machine Learning. Also, I have very good knowledge of software design methodologies, information systems architecture, object oriented design, and software design patterns. Teaching is my passion. I hope you will enjoy my course.