Text Pre-processing using NLTK and Python | DataHour by Dr. Nitin Shelke

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. Stay on top of your industry by interacting with us on our social channels: Follow us on Instagram: https://www.instagram.com/analytics_vidhya/ Like us on Facebook: https://www.facebook.com/AnalyticsVidhya/ Follow us on Twitter: https://twitter.com/AnalyticsVidhya Follow us on LinkedIn:https://www.linkedin.com/company/analytics-vidhya