Machine Learning - Stanford University

This are my exercises for Machine Learning from Stanford University. Taught by: Andrew Ng, Associate Professor, Stanford University.

For reference only. Please do not copy my exercises.

https://www.coursera.org/learn/machine-learning/

Final personal mark

Assignments passed: 25/25

Final grade: 97.6%

Course summary

Week 1

• 1. Introduction
• 2. Linear Regression with One Variable
• 3. Linear Algebra Review

Week 2

• 4. Linear Regression with Multiple Variables
• 5. Octave/Matlab Tutorial
• Exercise 1

Week 3

• 6. Logistic Regression
• 7. Regularization
• Exercise 2

Week 4

• 8. Neural Networks: Representation
• Exercise 3

Week 5

• 9. Neural Networks: Learning
• Exercise 4

Week 6

• 10. Advice for Applying Machine Learning
• 11. Machine Learning System Design
• Exercise 5

Week 7

• 12. Support Vector Machines
• Exercise 6

Week 8

• 13. Unsupervised Learning
• 14. Dimensionality Reduction
• Exercise 7

Week 9

• 15. Anomaly Detection
• 16. Recommender Systems
• Exercise 8

Week 10

• 17. Large Scale Machine Learning

Week 11

• 18. Application Example: Photo OCR