How kaspergl/ml26 works
This repository is a machine-learning course organized as weekly lessons, notebooks, exercises, and paired solution materials—not a deployed application. A learner’s broad workflow is to study a topic, work through its exercise or notebook, and consult solution directories where available. The sampled Python modules cover regression, nonlinear classification, and ensemble boosting. Most notebooks and README files were not excerpted, so their detailed contents and cross-week dependencies cannot be verified; dashed links indicate the high-level learner workflow rather than code calls.
Main entry points: week1 Python & sklearn · week1Solutions Week 1 Solutions · week5/theory.ipynb Week 5 Theory · week6/theory.ipynb Week 6 Theory
Components 20
Foundations
- Python & sklearn
week1 - Week 1 Solutions
week1Solutions - Week 5 Theory
week5/theory.ipynb - Week 6 Theory
week6/theory.ipynb
Core Models
- Regression Stumps
week2/regression_stumps.py - Stump Solutions
week2Solutions/regression_stumps.py - Linear Regression
week3/linear_regression.py - Regression Solutions
week3Solutions/linear_regression.py - Nonlinear Models
week4/code_nonlinear.py - Nonlinear Solutions
week4Solutions/code_nonlinear.py - Bias & Variance
week7/BiasVariance.ipynb
Ensembles
- AdaBoost
week8/adaboost.py - Gradient Boosting
week8/gradientboost.py - Boosting Solutions
week8Solutions
Advanced Topics
- Week 9 Theory
week9/theory.ipynb - Week 10 Exercises
week10/Exercises.ipynb - Week 12 Theory
week12/theory.ipynb - Skip-gram
week13/skipgram.ipynb - Hand-in Assignments
handins
Other components
- Learner
Connections 19
- Learner → Python & sklearn: studies
- Learner → Regression Stumps: practices
- Learner → Linear Regression: practices
- Learner → Nonlinear Models: practices
- Learner → Week 5 Theory: studies
- Learner → Week 6 Theory: studies
- Learner → Bias & Variance: studies
- Learner → AdaBoost: practices
- Learner → Gradient Boosting: practices
- Learner → Week 9 Theory: studies
- Learner → Week 10 Exercises: completes
- Learner → Week 12 Theory: studies
- Learner → Skip-gram: practices
- Learner → Hand-in Assignments: submits
- Learner → Week 1 Solutions: consults
- Learner → Stump Solutions: consults
- Learner → Regression Solutions: consults
- Learner → Nonlinear Solutions: consults
- Learner → Boosting Solutions: consults