Start here: portal to the lectures
（每一天都对应一个链接，包含videos 和materials）
Each of the pages linked below represents one day of the school, and contains the links to the lecture videos and other materials. The instructors(讲师) names are given in parenthesis. Additional links will be added during the school‘s duration (Sep. 2-12, 2014). For a self-paced study, you do not have to follow these in this particular order, although there are some obvious logical sequences.
（点击day开始学习）
Click on the Day link, and then follow the links
shown on that page. Check out also our
general useful links.
Day 1:
- Introduction and a Broader Context (G. Djorgovski,
D. Crichton, R. Doyle) - Big Data Architecture: Fundamentals (C. Mattman)
- Introduction to Machine Learning (C. Donalek)
- Best programming practices (A. Mahabal)
- Content Detection and Analysis for Big Data (C.
Mattmann)
Day 3: Introduction to R (A.
Mahabal)
Day 4: Inference and
Uncertainty (A. Braverman)
Day 5: Databases (M.
Graham)
Day 6: Data
Visualization (S. Davidoff)
Day 7: Clustering and
Classification (C. Donalek)
Day 8: Decision Trees
and Random Forests (T. Fuchs)
Day 9: Dimensionality
Reduction (D. Thompson)