This repository contains material for SISBID module on Supervised Methods for Statistical Machine Learning.
Please note that the module numbers may change in different years when SISBID is offered. Therefore, the past material for this module are archived under the name "Module 4". However, the content corresponds to mateiral for the Supervised Machine Learning module.
We have pre-recorded some of the lectures. Links to these pre-recorded lectures are given below (the password for accessing these files will be sent to participants separately):
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SISBID Pre-Recorded Video 1: Introduction
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SISBID Pre-Recorded Video 2: R Lab 1
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SISBID Pre-Recorded Video 3: R Lab 2
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SISBID Pre-Recorded Video 4: Batch Effects
Please watch videos 1-3 (all related to the first set of slides, SISBID1.pdf) before the first class. You can watch video 4, on batch effects, at any point -- we wil briefly go over the topic after the lecture on classification, but will not discuss it extensively.
Finally, here is one more pre-recorded lecture:
- SISBID Pre-Recorded Video 5: slide set 6 (methods for other data types)
We will be using the mnist data for for deep neural net demos. This data set is too large to post on GitHub, but can be downloaded here.
Here are the videos from live lectures (password required):
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Day 1 (Monday July 31st, 8am-2:30pm PT): Regression+Classification
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Day 2 (Tuesday Aug 1st, 8am-2:30pm PT): Classification+Tree-Based Methods
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Day 3 (Wednesday Aug 2nd, 8am-11:30am PT): Deep Neural Nets