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Video status: Checked: no corresponding recording link listed on the public official page. Source details
Lab 2 in the official MIT 6.S191 2026 repository is Lab 2: From MNIST to Facial Debiasing with a DB-VAE. Part 1 classifies MNIST with dense and convolutional networks; Part 2 learns a facial latent distribution with a DB-VAE and changes training sampling. This article pins the 2026 branch so later changes to master do not silently alter the exercise.
Before you begin
The official 2026 README specifies Google Colab, Python 3, and a GPU runtime. Copy the notebook to your Drive and run it from the beginning. Put API keys in the notebook's secret manager—never in a shareable cell or Git commit.
Recommended sequence
- Use Part 1 to verify convolution shapes and the training loop
- Record aggregate results and concrete failures from the baseline detector
- Compare the same cases after the DB-VAE without treating one metric as a fairness verdict
Solve one TODO at a time. Write the expected input and output shapes before executing the cell; when something fails, preserve the error and your reason for the fix. Public solutions are for final comparison, not initial copying.
Expected outputs include MNIST results, baseline face-detection results, and the same cases evaluated after DB-VAE resampling. Common failures include putting the image channel in the wrong dimension and reporting only aggregate accuracy without preserving failed face examples.
Completion criteria
Keep a notebook copy, one reproducible end-to-end run, and a short conclusion: what the model did correctly, where it failed, and which variable you would change next. A service-dashboard screenshot does not replace model outputs and an experiment record.
Limits
This is a course experiment, not a fairness fix proven across all populations. Data, measurement, and deployment context still require a separate audit.
Course video sources
Rechecked against the live official course page on 2026-10-10: the public page lists lecture recordings only and no recording dedicated to this article (the lab is provided as official GitHub notebooks).
Course and recording entries:
Checked: 2026-10-10.
Update Log
- 2026-10-10: Added explicit video status and checked recording sources and access notes.
- 2026-10-10: Rechecked video status. Live-checked the official public page: it still lists lecture recordings only, with none dedicated to this article, so the status is now “Checked: no corresponding recording link listed on the public official page.”
References
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