This repository documents my step-by-step learning and implementation of modern MLOps, AI Infrastructure, and Cloud-Native ML systems.
This library help to create models with identifiers, checkpoints, logs and metadata automatically, in order to make the training process more efficient and traceable.
this is website for machine learning steps
This folder contains my Individual Task reports for Fundamentals of AI & ML (B.Tech). It covers Human, Animal, and Machine Intelligence, Data Essentials with Big Data and ethics, and Feature Extraction in Machine Learning. Each report explains key concepts, methodologies, and practical insights.
An automated system for generating educational ML concept animations from text descriptions using Manim.
This project simulates a production-grade MLOps pipeline inspired by real-world ML workflow automation and monitoring systems.
In today's fast-paced world, efficient food delivery is crucial. This project presents a robust and modular end-to-end machine learning pipeline designed to predict food delivery times. By leveraging a rich dataset containing delivery personnel details, restaurant locations, order information, and environmental factors like weather and traffic.
A beginner-friendly Logistic Regression project that predicts student pass/fail outcomes based on study hours and demonstrates the complete machine learning classification workflow.
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