Stanford Machine Learning course on Coursera
A concise ML course offered by Andrew Ng, Stanford University and delivered via Coursera. Programming exercises come in script format and are supported by a detailed pdf documents. Expected intermediate results are printed to the console as checkpoints.
Programming language: Matlab / Octave
Price: 99 AUD
Syllabus:
- Week 1:
- Introduction (2h)
- Linear Regression with One Variable (2h)
- Linear Algebra Review (2h)
- Week 2:
- Linear Regression with Multiple Variables (3h)
- Octave/Matlab Tutorial (5h)
- Week 3:
- Logistic Regression (2h)
- Regularization (5h)
- Week 4:
- Neural Networks: Representation (5h)
- Week 5:
- Neural Networks: Learning (5h)
- Week 6:
- Advice for Applying Machine Learning (5h)
- Machine Learning System Design (2h)
- Week 7:
- Support Vector Machines (5h)
- Week 8:
- Unsupervised Learning (1h)
- Dimensionality Reduction (5h)
- Week 9:
- Anomaly Detection (2h)
- Recommender Systems (5h)
- Week 10:
- Large Scale Machine Learning (2h)
- Week 11:
- Application Example: Photo OCR (2h)