Build ML systems
block by block.
Implement every component from scratch. Understand the math. Write the code. Stress-test your models like a production ML engineer.
Learn like a production ML engineer.
Not just implement models — understand failure modes, stability issues, distribution shifts, and performance tradeoffs.
First Principles
Code every block yourself — no black boxes.
Stress Testing
Evaluate under edge cases, drift, and noisy data.
System Thinking
Learn how models behave inside real-world systems.
Stay Current
Track latest architectures and modern ML practices.
Featured Problems
Master ML concepts one block at a time
Learning Tracks
From fundamentals to modern architectures.
Transformers: From Attention to Full Model
Build a complete Transformer from scratch in NumPy
Optimization: From First Principles to Momentum
Build gradient descent, regression and momentum from scratch.
Autonomous Driving - Perception
Build the vision system that sees the world
Master ML from first principles.
Train today. Benchmark tomorrow.
Early Beta • No credit card required
Coming Soon
More paths launching in the next few weeks
Transformer Decoder (GPT Style)
Build causal attention, decoder blocks, and complete GPT architecture from scratch.
Vision Models For Autonomous Driving Perception
Build the eyes of a self-driving car — object detection, lane segmentation, LiDAR, and sensor fusion.
Diffusion Models
Build DDPM, score-based models, and Stable Diffusion components from first principles.