[Online] State of Bayes Lecture Series #7 Gaussian Processes for Time Series
Details
šļø Speaker: Maxim Kochurov | ā° Time: 9am PT / 12pm ET / 6pm Berlin
State of Bayes is a series of webinars about advances in practical methods and modeling intuition. The major focus of the webinar series will be on understanding concepts of advanced statistical models and introducing prior knowledge into the loop. This free course will be interesting for Bayesian practitioners who want to deepen their understanding about Bayesian modeling.
In the closing webinar session we'll meet Gaussian processes for time series analysis.
There are some very enlightening applications that bring GP to the number one most useful models in practice:
- Most known are seasonality decompositions for time series.
- Less known but very useful is time varying parameter for a model (an example of that you can see here: https://www.pymc-labs.io/blog-posts/modelling-changes-marketing-effectiveness-over-time/)
During the webinar we'll get familiar with necessary concepts to apply a GP on a time series. At the coding session we'll revisit Rolling regression example from pymc-examples and will make that even more cool than ever before.
- Subscribe to our PyMCLabs YouTube to see past videos.
- Feedback Form: https://forms.gle/xHsaVzWrzDxRjhrt5
Sessions (generally bi-weekly)
The full course is:
- Session 1ļøā£: Introduction ā¶ļø L1: VIDEO
- Session 2ļøā£: Bayesian Thinking ā¶ļø L2: VIDEO
- Session 3ļøā£: Hierarchical modeling ā¶ļø L3: VIDEO
- Session 4ļøā£: Interpretable Linear Regressions ā¶ļø L4: VIDEO
- Session 5ļøā£: Bayesian AB testing ā¶ļø L5: VIDEO
- Session 6ļøā£: Gaussian Processes ā¶ļø L6:VIDEO
- Session 7ļøā£: Gaussian Processes for Time Series (6th July)
š¼ About the speaker:
- Maxim Kochurov
Maxim is a core developer of PyMC, a probabilistic programming language. Since the foundation of PyMC Labs he helps to improve complex statistical models and create a reusable solution. Besides strong expertise in Bayesian modeling his background includes economics, software engineering, and large-scale computer vision.
š Connect with Maxim:
š LinkedIn: https://www.linkedin.com/in/ferrine
š Twitter: https://twitter.com/ferrine96
š GitHub: https://github.com/ferrine
š Website: https://ferrine.github.io
š Code of Conduct:
Please note that participants are expected to abide by PyMC's Code of Conduct.
š Connecting with PyMC Labs:
š„ LinkedIn: https://www.linkedin.com/company/pymc-labs/
š¦ Twitter: https://twitter.com/pymc_labs
š„ YouTube: https://www.youtube.com/c/PyMCLabs
š¤ Meetup: https://www.meetup.com/pymc-labs-online-meetup/
š Connecting with PyMC Open Source:
š¬ Q&A/Discussion: https://discourse.pymc.io
š GitHub: https://github.com/pymc-devs/pymc
š¼ LinkedIn: https://www.linkedin.com/company/pymc/mycompany
š„ Twitter: https://twitter.com/pymc_devs
šŗ YouTube: https://www.youtube.com/c/PyMCDevelopers
š Meetup: https://www.meetup.com/pymc-online-meetup/
