Welcome
Step into my digital workspace — a place built for exploration, experimentation, and continuous learning. This site brings together the tools, demos, and notes that shape my journey through programming, machine learning, and agentic systems.
What You’ll Find Here
This site is organized around three core pillars:
• The Blog — long‑form explanations, project breakdowns, and reflections on what I’m learning.
• The Learning Hub — Python, JavaScript, neural networks, regression tools, and interactive demos.
• Project Notebooks — GitHub repositories and Kaggle notebooks for every major experiment.
Explore the Learning Hub
The Learning Hub is where the hands‑on learning happens. It brings together clear notes, practical references, and interactive tools so you can build intuition step by step — from basic Python and JavaScript all the way to multi‑feature regression and neural networks.
Inside the Learning Hub you’ll find:
• Python notes and reference material
• JavaScript notes and reference material
• A full sequence of neural network learning projects
• A single‑input linear regression tool
• A 3D multi‑feature regression simulator
Each resource is designed to help you understand not just the formulas, but the geometry and intuition behind them. Whether you're adjusting weights in a regression model or exploring how neurons stack to solve nonlinear problems, the Learning Hub gives you a place to experiment, visualize, and learn by doing.
Projects, GitHub, and Kaggle
Every neural network project includes:
• A detailed blog walkthrough
• A GitHub repository with clean code
• A Kaggle notebook you can run instantly
You can explore the full collection here:
First‑Principles Focus
Here you’ll find interactive Python notebooks, mathematical deep dives, and hands‑on explorations that trace machine learning from its historical roots to modern neural networks. The focus here isn’t just on using ML tools — it’s on understanding them from first principles.
Whether you're studying linear regression, unpacking the geometry behind gradient descent, exploring the evolution of early perceptrons, or breaking down neural networks into their core mathematical components, this hub is built to make every concept transparent and intuitive.
I invite you to learn alongside me. This hub grows as I grow — one concept, one experiment, and one breakthrough at a time.