NLP Tutorial 1 – Spam Text Message Classification using NLP, sklearn | Natural Language Processing

Dataset: https://github.com/laxmimerit/All-CSV-ML-Data-Files-Download

In this video, we will learn about spam text message classification using NLP. Natural Language Processing (NLP) is the field of Artificial Intelligence, where we analyze text using machine learning models. Text Classification, Spam Filters, Voice text messaging, Sentiment analysis, Spell or grammar check, Chatbot, Search Suggestion, Search Autocorrect, Automatic Review, Analysis system, Machine translation are the applications of NLP.

Tokenization is breaking the raw text into small chunks. Tokenization breaks the raw text into words, sentences called tokens. These tokens help in understanding the context or developing the model for the NLP. The tokenization helps in interpreting the meaning of the text by analyzing the sequence of the words.

🔊 Watch till last for a detailed description
03:33 What is NLP?
09:38 Natural Language generation
12:42 Installing packages
21:11 Bag of words
27:07 Get started with Code
32:05 Balance the data
37:16 Exploratory data analysis
49:08 Pipeline and random forest
58:41 Support vector machine

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