End-to-End AI Engineering

Building AI systems to understand them better.

I am an AI/ML Engineer & Full Stack Developer. I build end-to-end projects—from the math of Transformers to the UI—and I share the code, the concepts, and the mistakes here so we can learn together.

~/projects/ai-systems

class TransformerEngine:

def __init__(self):

self.attention = MultiHeadAttention()

self.ffn = FeedForward()

▋Building...

I Build to Learn. I Teach to Master.

You don't truly understand a concept until you can build it from scratch.

This platform is my digital garden. It is where I share the articles, tutorials, tools, and projects I build to document my learning journey.

Whether you are a student trying to visualize a Tokenizer or a developer integrating Open Weight models, I hope these resources make the concepts clearer for you.

Explore the Platform

Three Pillars of Learning

The Classroom

Structured guides breaking down complex AI concepts into clear, step-by-step tutorials. Theory translated into production code.

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The Playground

Interactive experiments and visualizers. See how algorithms like BPE tokenization and Q-Learning actually work under the hood.

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The Dev Log

Engineering notes on system design, architecture patterns, MLOps, and the challenges of deploying AI models to production.

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Proof of Work

Featured Engineering

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Visual Tokenizer (BPE)

NLP / Education

Educational tool to visualize how models like GPT-4 break down text. Debug token usage and understand costs.

Privacy Shield

Computer Vision

Computer vision tool that detects sensitive data in images and automatically blurs them for secure sharing.

Local RAG Assistant

LLM / RAG

Secure chat interface connecting Open Weight models (Llama 3) to your private documents. 100% local.

Stock Screener

Finance / NLP

Financial tool aggregating real-time news sentiment and filtering stocks based on investment criteria.

Join the System

Join the Engineering Log

Receive practical insights on building end-to-end AI systems. Code, architecture decisions, and lessons learned.