About
This repository is a related to all about Natural Langauge Processing - an A-Z guide to the world of Data Science. This supplement contains the implementation of algorithms, statistical methods and techniques (in Python)
Contribution: We would love your help in making this repository even better! If you know of an amazing AI course that isn't listed here, or if you have any suggestions for improvement in any repository content, feel free to open an issue or submit a repository contribution request.
Together, let's make this the best AI learning hub website! 🚀
https://coursesteach.com/
https://coursesteach.com/course/view.php?id=46
Week 0-📚Chapter 1:Introduction
- What is Natural Language Processing (NLP)(Tutorial
- Natural Language Processing Tasks and Applications-Tutorial
- Best Free Resources to Learn NLP-Tutorial
- Preprocessing_Aassignment_1.ipynb
- Supervised ML & Sentiment Analysis(Tutorial)
- Vocabulary & Feature Extraction(Tutorial)
- Negative and Positive Frequencies(Tutorial)
- Text pre-processing
- Putting it All Together
- Logistic Regression Overview
- Logistic Regression: Training
- Logistic Regression: Testing
- Logistic Regression: Cost Function
- Lab#1:Visualizing word frequencies
- Lab 2:Visualizing tweets and the Logistic Regression model
- Assignmen:Sentiment analysis with logistic Regression
Week 3 -📚Chapter 3:Vector Space Model
- Lecture Notebook - Working with text files
- Lecture Notebook - Working with tags and Numpy
- Assignment: Part of Speech Tagging
- Assignment 2: Parts-of-Speech Tagging (POS)