https://github.com/florasteve/ml-foundations-day1
Day-1 ML foundations focused on linear algebra: vectors, dot products, norms, angles, projections, and basic matrix operations—implemented in a Jupyter notebook with NumPy/Matplotlib, clear 2D visuals, a self-quiz, and a brief reflection. Emphasizes how these math primitives map to core ML/AI ideas (similarity, least squares, geometric transforms).
https://github.com/florasteve/ml-foundations-day1
ai data-science education jupyter-notebook linear-algebra machine-learning matplotlib numpy python3 terminal-mac tutorial visualization vscode
Last synced: about 2 months ago
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Day-1 ML foundations focused on linear algebra: vectors, dot products, norms, angles, projections, and basic matrix operations—implemented in a Jupyter notebook with NumPy/Matplotlib, clear 2D visuals, a self-quiz, and a brief reflection. Emphasizes how these math primitives map to core ML/AI ideas (similarity, least squares, geometric transforms).
- Host: GitHub
- URL: https://github.com/florasteve/ml-foundations-day1
- Owner: florasteve
- Created: 2025-09-05T17:19:34.000Z (10 months ago)
- Default Branch: main
- Last Pushed: 2025-09-05T18:31:58.000Z (10 months ago)
- Last Synced: 2025-09-05T20:31:05.620Z (10 months ago)
- Topics: ai, data-science, education, jupyter-notebook, linear-algebra, machine-learning, matplotlib, numpy, python3, terminal-mac, tutorial, visualization, vscode
- Language: Jupyter Notebook
- Homepage:
- Size: 107 KB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# ML Foundations — Day 1 Starter
This repository scaffolds **Month 1 / Day 1** of your Core ML & Data Foundations plan.
## What you’ll do today
- Set up a clean Python environment (virtualenv)
- Practice linear algebra with NumPy: vectors, dot product, norm, angle, projection
- Practice matrix ops: identity, inverse, determinant, matrix–vector, matrix–matrix
- Plot 2D vectors and a simple linear transformation with Matplotlib
- Save figures to `figures/`
- Write a short reflection in the notebook
- Commit your work with Git
## How to run
1. Open a terminal (or PowerShell on Windows) and navigate to this folder.
2. Create & activate a virtual environment, then install dependencies:
- macOS/Linux:
```bash
python3 -m venv .venv
source .venv/bin/activate
pip install --upgrade pip
pip install -r requirements.txt
```
- Windows (PowerShell):
```powershell
py -3 -m venv .venv
. .venv\Scripts\Activate.ps1
python -m pip install --upgrade pip
pip install -r requirements.txt
```
3. Start Jupyter and open the Day 1 notebook:
```bash
jupyter notebook notebooks/01_linear_algebra_basics.ipynb
```
Figures you create will be saved into `figures/`.