The Caltech-JPL Summer School on Big Data Analytics

The anticipated schedule of lectures (subject to changes):

Each bullet bellow corresponds to a set of materials that includes approximately 2 hours of video lectures, various links and supplementary materials, plus some on-line, hands-on exercises.

1. Introduction to the school.  Software architectures.  Introduction to Machine Learning.

2. Best programming practices.  Information retrieval.

3. Introduction to R.  Markov Chain Monte Carlo.

4. Statistical resampling and inference.

5. Databases.

6. Data visualization.

7. Clustering and classification.

8. Decision trees and random forests.

9. Dimensionality reduction.  Closing remarks.