Track
Python for ML
Goal: NumPy, notebooks, data frames, plotting.
Prereqs: none
Status: done
Work through the steps in order. Bold links open YouTube.
| Step | Concept | YouTube | Read |
|---|---|---|---|
| 1 | Jupyter notebooks | Corey Schafer — Jupyter Notebook Tutorial | |
| 2 | Lists vs arrays | PDSH — Understanding Data Types in Python | |
| 3 | NumPy arrays | Keith Galli — Complete Python NumPy Tutorial | NumPy — the absolute basics for beginners |
| 4 | Vectorized ops | PDSH — Computation on NumPy Arrays: Universal Functions | |
| 5 | Broadcasting | NumPy — Broadcasting | |
| 6 | Boolean masks | PDSH — Comparisons, Masks, and Boolean Logic | |
| 7 | Pandas | Keith Galli — Complete Python Pandas Tutorial (2025) | 10 minutes to pandas |
| 8 | Matplotlib | Corey Schafer — Matplotlib Tutorial (Part 1) | Matplotlib — Quick start guide |
| 9 | NumPy in a notebook | CS231n — Python Numpy Tutorial |
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