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Basic Machine Learning

Name: Basic Machine Learning
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with LaunchFar

21 lessonsabout 7 hours total

Build the intuition to choose a model, judge whether it actually works, and ship it without leaking your evaluation into the fit.

For: Engineers and analysts who already call ML libraries and want to know what the fit is doing.
You need: Comfortable reading Python. Each lesson starts with a visual, then moves to a short lab in your browser.

Learn essential machine-learning models through animated calculations, intuitive experiments, and tiny guided Python notebooks.

Syllabus

7 tracks · 7 modules · 21 lessons

How Models Learn

Split data so the score you report means something, and follow a loss downhill step by step to see what fitting actually does.

1 module · 3 lessons

1. The learning loop
- The Learning Loop20 min
- Training and Holdout Data14 min
- Loss and Gradient Descent16 min

Fit a line, judge it against a baseline with MAE, RMSE and R², and pick a polynomial degree on validation error rather than training fit.

1 module · 3 lessons

2. Regression foundations
- Linear Regression32 min
- Bias, Variance, and Polynomial Fit22 min

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