All the material from the Udemy course "Beyond Jupyter Notebooks"

Contains a collection of my experimentations, explorations, and data analysis of random datasets

Successfully developed a machine learning model which can accurately predict up to 100% accuracy whether a credit card application of a given applicant would be approved or not, based on several demographic features such as applicant age, total income, marital status, total years of work experience, etc.

Built to showcase end-to-end ML Ops practices including data ingestion, monitoring, drift detection, automated retraining, and model promotion in a single integrated pipeline.

Successfully established a machine learning model that can accurately predict the sales of a superstore based on various features such as quantity, profit, discount, postal code, etc. The features are mainly associated with order details and customer demographics.

Production-grade real-time ML platform designed for automated data ingestion, feature engineering, model training, drift detection, and continuous retraining. Includes modular pipelines, monitoring dashboards, and live inference capabilities, enabling scalable, reliable, and feedback-driven machine learning in production environments.

CarPriceAI is an app that predicts car prices based on their characteristics using a machine learning model. It also features a virtual assistant that provides interactive information about cars through a RAG system.