This is GEM repo, as it has all the Hands-On ML notebooks

In this notebook, we will be performing machine learning on the Big mart sales dataset

XGBoost-based stock price prediction with technical indicators, rolling-window training, and full evaluation pipeline in a Jupyter Notebook.

This is a reviewed notebook to the DSN AI+ OAU July 2020 challenge where I took the first position. The project demonstrate proper Exploratory Data Analysis, categorical data handling, Data visualization, feature selection and engineering, Model selection and hyperparameter tuning of various regression algorithms.

Regression Machine Learning Project

End-to-end, multi-phase ML pipeline for smart industrial water quality monitoring/managing. covering classification, anomaly detection, predictive maintenance, and parameter forecasting. Implemented in Python and Jupyter; includes reproducible notebooks, deployable model artifacts and ready connectors for real-time integration (Flask, Node-RED).

This Project is a research on AirBnB house price prediction of 5 States in the USA. It Contains a Jupyter notebook which gives a detailed analytics of the house prices.

This notebook is my answer to the Housing Price Competition that is being held in https://www.kaggle.com/competitions/home-data-for-ml-course/overview. Please import the .ipynb file on kaggle environment for it to work.