This is Krish Naik Sir's GitHub repository, which I forked. It contains comprehensive resources and materials for data science, including his YouTube video tutorials and open-source contributions.

Sharing the AIML resources I use

Complete NLP for Machine Learning course by Krish Naik with Python, NLTK and SpaCy implementations

A web app that predicts air quality using machine learning. It integrates real-time location data via APIs, processes it through a modular pipeline, and provides predictions with dynamic suggestions for locations. Built with Flask for the frontend and modular Python code for data processing and model inference.

This application is designed to extract information from uploaded invoice images and provide detailed responses based on user prompts. It leverages the Google Gemini-1.5-flash model for generating content and analyzing the invoice data.

Hands-on ML implementation following Krish Naik's Complete ML & Data Science Bootcamp on Udemy

Code implementations from Krish Naik's NLP YouTube playlist

Implementation of Support Vector Machines (SVM) in Machine Learning, including kernel methods, classification, and Support Vector Regression (SVR) with visualizations and step-by-step workflow.

compact, hand-written notes to learn statistics — from probability distributions to inference and the Central Limit Theorem.

Code implementations from Krish Naik's NLP YouTube playlist