Thinking About Data

1. Overview? : PDF Video
2. What is Machine Learning? : PDF Video
3. What is Classification? : PDF Video
4. What is Regression? : PDF Video
5. What is Clustering? : PDF Video
6. Attribute-value representation : PDF Video
7. Categorical (nominal) Attributes  : PDF Video
8. Ordinal Attributes : PDF Video
9. Numerical Attributes and Outliers : PDF Video
10. Skewed and Non-Monotonic Attributes : PDF Video
11. Credit Scoring Example : PDF Video
12. How to Represent Images : PDF Video
13. Representing Handwritten Digits : PDF Video
14. Why Blurring Helps Machine Learning : Video
15. When do Pixels Work as Attributes : PDF Video
16. Attributes for Object Recognition : PDF Video
17. Representing Text: Categorical Attributes : PDF Video
18. Representing Text: Numerical Attributes : PDF Video
19. Representing Music: Fourier Coefficients : PDF Video
20. Supervised vs. Unsupervised Learning : PDF Video
21. Binary vs Multiclass Classifiers  : PDF Video
22. Accuracy and Imbalanced Classes : PDF Video
23. Generative vs. Discriminative Learning : PDF Video
24. How to Represent Structured Objects : PDF Video
25. Detect Outliers by Visualising the Data : PDF Video

All Slides: PDF

Video Playlist Link

Embedded Video Playlist