Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

Add timestamps for video 29: Luciano #25

Merged
merged 3 commits into from
Jul 10, 2022
Merged

Add timestamps for video 29: Luciano #25

Changes from 1 commit
Commits
Show all changes
3 commits
Select commit Hold shift + click to select a range
71d60da
Add timestamps for Luciano
zbraiterman Jul 7, 2022
a2f9560
add leading zero
reshamas Jul 10, 2022
8e254a6
formatting of time
reshamas Jul 10, 2022
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
21 changes: 19 additions & 2 deletions videos-list/29-luciano.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -14,8 +14,25 @@ https://discourse.pymc.io/t/posterior-predictive-sampling-in-pymc3-by-luciano-pa

## Timestamps
- 0:00 Start of event
reshamas marked this conversation as resolved.
Show resolved Hide resolved
- x:xx
- x:xx
- 0:22 Background on PyMC3 common workflow and posterior predictive distribution
- 2:56 What is this presentation about?
- 3:19 Simple model without posterior predictive problems
- 4:27 Create train and test data
- 5:12 Translate the math into PyMC3
- 6:52 Visualize and plot the model and predictions
- 8:20 Make predictions on the new data
- 9:29 Shape problems
- 12:46 A simple extension of linear regression
- 17:26 View the results of the extension
- 17:50 Error on the test data
- 19:15 What happens if we try to marginalize label out of the model?
- 21:38 Shape problem with the test data
- 22:55 Solution, a functional approach
- 27:50 Factory functions aren’t a silver bullet
- 28:12 Manually trim the inferred posterior
- 29:22 Challenges with sampling
- 32:10 How can PyMC help?
- 32:45 Conclusion
reshamas marked this conversation as resolved.
Show resolved Hide resolved

## Note: help us add timestamps here
https://github.com/pymc-devs/video-timestamps
Expand Down