causal-inference-studies
Explaining the main concepts around causal learning via bitesize theory and code!
Introduction
| Number | Lesson | Complexity |
|---|---|---|
| 01 | Why causality matters | 🍰 |
| 02 | Association vs causation | 🍰 |
| 03 | Confounders | 🍰 |
| 04 | Simpson's paradox | 🍰 |
Core concepts
| Number | Lesson | Complexity |
|---|---|---|
| 05 | DAGs | 📚 |
| 06 | DAGs 2 | 📚 |
| 07 | Causal effects | 🍰 |
| 07 | Feature selection | 🍰 |
Miscellaneous
| Number | Lesson | Complexity |
|---|---|---|
| 06 | DAGs with math | 🎓 |
| 08 | Causal questions | 💭 |
| 09 | Attribution | 🎓 |
| 10 | Causal assumptions | 🎓 |
| 11 | A/B testing | 🎓 |
| 12 | Causality and time | 💭 |
| 13 | Shapley values | 🎓 |
Complexity score:
- 🍰: a piece of cake
- 📚: requires thinking about it
- 🎓: requires connecting dots
- 💭: it's philosophy