Data-driven Computer Science UoB
- Laurence Aitchison [[email protected]] (unit director)
- Majid Mirmehdi [[email protected]]
Holly Milllea | Amirhossein Dadashzadeh | Faegheh Sardari | Jonathan Munro | Vangelis Kazakos | Zhaozhen Xu
Lecture videos for a week will be released on Monday and posted here. Please take a look at them promptly!
The coursework will be 40% of the mark and the exam will be 60% (deadlines TBA).
TA led sessions on Thursday 3-5 are the main route for feedback on all aspects of the course: lectures, labs and coursework. These will start on 11th Feb, and you will be assigned a group by email before then. They will be hosted through the public Teams group [grp-COMS20011_2020] (if the link doesn't work, just search for "grp-COMS20011_2020").
There are lecturer-led Q&A sessions on Mondays at 4pm. The first of these (Feb 1st) will be TA led, to help getting IT set up for labs.
There will be "lab" exercises released in the "lab" folder. Please do them promptly and bring any questions to the TA-led sessions: the coursework is heavily based on the labs!
Data Acquisition & Pre-processing
| Lecture | video | slides |
|---|---|---|
| 1. Intro to COMS20111 - very fishy | [Stream link] | [pdf] |
| 2. Intro - Part 2 - example projects | [Stream link] | [pdf] |
| 3. Data Acquisition - Sampling - Acquisition | [Stream link] | [pdf] |
| 4. Data Characteristics - Distance Measures | [Stream link] | [pdf] |
| 5. Data Characteristics - Covariance - Eigen Analysis - Outliers | [Stream link] | [pdf] |
| Problem Sheet 1 Updated - New Q 12/02/21 | Self/Group study | [pdf] |
| Problem Sheet 1 Updated - New Q/A 12/02/21 | Answers | [pdf] |
| Q&A Session | [Stream link] | - |
| Lecture | video | slides |
|---|---|---|
| 1. Maximum likelihood for a coin | [Stream link] | [notebook 1] |
| 2. Bayes for a coin | [Stream link] | [notebook 1] |
| 3. Intro to supervised learning | [Stream link] | [notebook 2] |
| 4. Linear regression derivation | [Stream link] | [notebook 2] |
| Problem Sheet W14 | [pdf] | |
| Q&A Session | [Stream link] | - |
| Lecture | video | slides |
|---|---|---|
| 1. Linear regression examples | [Stream link] | [notebook 2] |
| 2. Overfitting | [Stream link] | [notebook 3] |
| 3. Cross-validation | [Stream link] | [notebook 3] |
| 4. Regularisation | [Stream link] | [notebook 3] |
| Problem Sheet W15 | [notebook] |
I have printed the Notebooks as pdfs. Note that this really doesn't work well, as many of the interactive plots can't be printed.
| Notebook |
|---|
| [notebook 1] |
| [notebook 2] |
| [notebook 3] |