DataHour: Text Pre-processing using NLTK and Python

DataHour Recording

Find the resources used in the DataHour HERE.

About the DataHour:

Text preprocessing is an important step for any Natural Language Processing (NLP) application. The text must be pre-processed before a model is trained for almost all AI and NLP based tasks. 

In this DataHour, Nitin will discuss several popular pre-processing approaches using NLTK and Python: lowercase, removing punctuation, tokenization, stopword filtering, stemming, lemmatization, Removal of URLs, Removal of HTML Tags, and Spelling Correction.

Topics which will be covered in this DataHour includes:

• NLP and Its Applications
• Operations on Text Data with Python and NLTK
• Text Pre-processing Steps
• Case Study based on Text Pre-processing

Prerequisites: Curiosity of learning Data Science and basic understanding of python programming.

Who is this DataHour for?

• Students & Freshers who want to build a career in the Data-tech domain.
• Working professionals who want to transition to the Data-tech domain.
• Data science professionals who want to accelerate their career growth

Speaker:

Dr. Nitin Shelke

Assistant Professor at the School of Computer Science Engineering and Technology, Bennett University (Times of India Group)

Dr. Nitin Arvind Shelke is an Assistant Professor at the School of Computer Science Engineering and Technology, Bennett University (Times of India Group) Greater Noida. He has extensive work experience in research, teaching, corporate training, and as a consultant data scientist with multiple organizations in the past. He received Ph.D. in Computer Science and Engineering from TIET, Patiala. His research interests include Machine Learning, Deep Learning, Multimedia Security, and NLP, with multiple publications in SCI journals and International Conferences. He has one patent granted by the Australian Govt and has published two patents in Indian Patent Journal.

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