Pattern is
Everything
Have you noticed the same shapes keep appearing — in data, in price charts? The bell curve in market returns. Gradient descent rolling downhill. A head-and-shoulders pattern at a reversal. This is a map of those recurring structures — 249 interactive, visual references across machine learning and markets.
New Here? Start With These
Start Here Path
Beginner → Build → Advanced
Normal Distribution
Machine Learning → Statistics
Gradient Descent
Machine Learning → ML Math
SHAP Values
Machine Learning → The Toolkit
Real-Data Cases
Build → Dataset → Model → Metrics
Head & Shoulders
Markets → Chart Patterns
Tokenization
Machine Learning → LLM Engineering
Sharpe Ratio
Machine Learning → The Toolkit
A quick tour of the site
249
Core Topics
249
Core Visualizations
3
Universes
10
Collections
Live Interactive Preview
Normal distribution — drag the sliders inside any topic · Try it →
📐 Interactive canvas diagrams
📝 Core formulas explained
🐍 JupyterLite notebooks
📊 Real-data mini-cases
🎛️ Draggable parameters
🌙 Dark mode
⚡ Zero dependencies
Learning Paths — Guided Progression
Beginner
ML Fundamentals
Start from zero — distributions, metrics, and your first model evaluation. No prior ML experience needed.
- Distribution Shape — know your data
- Gradient Descent — how models learn
- Confusion Matrix — measuring results
- ROC & AUC — comparing models
- Cross-Validation — honest evaluation
~45 min · 5 topics
Build
First Real-Data Model
Move from visual intuition into a practical workflow: dataset, split, model, metric, and failure mode.
- Housing Regression — start with tabular data
- Regression Metrics — measure error clearly
- Cross-Validation — evaluate honestly
- SHAP Values — inspect model behavior
- ML Lab — experiment by hand
~60 min · case + 4 topics
Intermediate
Time Series Mastery
From stationarity to forecasting — the full pipeline for time-dependent data.
- Stationarity — is your data ready?
- ARIMA — classical forecasting
- Prophet — fast, practical forecasting
- Walk-Forward Validation — test honestly
- Anomaly Detection — find the unusual
~60 min · 5 topics
Advanced
LLM Engineering
From tokenization to RLHF — understand and build with large language models.
- Tokenization — how text becomes numbers
- Self-Attention — the core mechanism
- RAG — retrieval-augmented generation
- RLHF — aligning models
- Quantization — making it fast
~90 min · 5 topics
Beginner
Market Intuition
Understand how markets move — risk, psychology, and the patterns traders watch. Evidence levels clearly marked.
- Fear & Greed — market emotions
- Value at Risk — quantifying danger
- Moving Averages — trend detection
- Sharpe Ratio — risk-adjusted returns
- Support & Resistance — price levels
~45 min · 5 topics
◆ The Pattern
A bell curve in model outputs, a head-and-shoulders on a chart — the same structural principle, different data. Every topic here makes that connection visible.
Universes
Machine Learning
149 topics across five collections — ML Math, The Toolkit, LLM Engineering, MLOps, and Timeseries Engineering. From linear algebra to production deployment, with interactive visualizations and code.
Market Patterns
100 topics across four collections — Chart Patterns, Technical Indicators, Market Psychology, and Risk & Portfolio. Visual guides to the patterns that move markets.
Pattern Essays
8 short, calm reflections on patterns that appear across the world — the bell curve, regression to the mean, the long tail, signal and noise, models vs reality, feedback loops, random walks, and thresholds. Each with an interactive visualization.
Real-Data Cases
4 practical mini-cases that connect the visual references to datasets, pipelines, metrics, failure modes, and notebook-ready starting points.