This is my repo for Machine learning from scratch from very scratch from Mathematics ( Basic alegbra --> Linear Alegbra --> Calculus -->Probability -->Statistics ) Then I will start Machine Learning then I will move to Deep LEARNING and Making Machine Learning Models and projects as well

My Machine Learning learning journey (Jan–Mar 2026)

Python projects and machine learning labs documenting my 2026 ML learning journey.

Personal AI & Data Science learning lab. Documenting my journey through Python, Machine Learning fundamentals, and AI experiments in 2026

Machine Learning lab notebooks using Python, built for GSoC 2026 and to document my learning journey toward building real-world ML solutions.

Structured journey toward mastering Data Structures, Machine Learning, Deep Learning, and MLOps. Target: 500 LeetCode problems, GSoC 2026, and elite AI engineering level.

This Repository will contain my whole 1.5 years of preparation and learnings about AI, Machine Learning and Deep Learning. From Basics of Python to Advanced application of Machine Learning and Deep Learning and other AI stuffs. I will be story telling my whole journey from 2026 January to 2027 July.

This repository contains my complete learning journey of Artificial Intelligence and Machine Learning in 2026. It includes concepts, notes, hands-on projects, coding implementations, and real-world applications to become an AI/ML Engineer.

A structured AI Engineer learning journey covering Python, Data Structures, Machine Learning, Deep Learning, NLP, Computer Vision, GenAI, Agentic AI, MLOps, and Cloud (AWS/Azure). Includes weekly learning notes, hands-on projects, experiments, and end-to-end implementations aligned with the 2026 AI Engineer roadmap.

Every expert starts somewhere. Started in 2026, this repository documents my journey as a student learning Python, Machine Learning, and real-world problem solving step by step. It serves as a living portfolio of daily learning, practice code, experiments, mistakes, and continuous improvement using Git and open-source tools.