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[Online] State of Bayes Lecture Series: Session 6 Gaussian Processes 2023-06-22 · 16:00 🎙️ Speaker: Maxim Kochurov \\| ⏰ Time: 9am PT / 12pm ET / 6pm Berlin Gaussian Processes are probably the most powerful models you can encounter in Bayesian statistics. To apply them, you first need to get familiar with the basics and first principles. While complicated formulas are awesome, we'll more focus on intuition and possible applications. In this lesson, you'll know what is a kernel how to think about kernel parameters how to make gaussian process hierarchy And a bonus, we'll lead a coding session where we apply a Gaussian process to analyze unbalanced stratified poll data. 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. Subscribe to our PyMCLabs YouTube to see past videos. Feedback Form: https://forms.gle/xHsaVzWrzDxRjhrt5 Sessions (generally bi-weekly) The full course is: Session 1️⃣: Introduction ▶️ L1: VIDEO Session 2️⃣: Bayesian Thinking ▶️ L2: VIDEO Session 3️⃣: Hierarchical modeling ▶️ L3: VIDEO Session 4️⃣: Interpretable Linear Regressions ▶️ L4: VIDEO Session 5️⃣: Bayesian AB testing ▶️ L5: VIDEO Session 6️⃣: Gaussian Processes (22th June, 2023) Session 7️⃣: Gaussian Processes for Time Series 💼 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. 🔗 Connect with Maxim: 👉 LinkedIn: https://www.linkedin.com/in/ferrine 👉 Twitter: https://twitter.com/ferrine96 👉 GitHub: https://github.com/ferrine 👉 Website: https://ferrine.github.io 📖 Code of Conduct: Please note that participants are expected to abide by PyMC's Code of Conduct. 🔗 Connecting with PyMC Labs: 👥 LinkedIn: https://www.linkedin.com/company/pymc-labs/ 🐦 Twitter: https://twitter.com/pymc_labs 🎥 YouTube: https://www.youtube.com/c/PyMCLabs 🤝 Meetup: https://www.meetup.com/pymc-labs-online-meetup/ 🔗 Connecting with PyMC Open Source: 💬 Q&A/Discussion: https://discourse.pymc.io 🐙 GitHub: https://github.com/pymc-devs/pymc 💼 LinkedIn: https://www.linkedin.com/company/pymc/mycompany 🐥 Twitter: https://twitter.com/pymc_devs 📺 YouTube: https://www.youtube.com/c/PyMCDevelopers 🎉 Meetup: https://www.meetup.com/pymc-online-meetup/	[Online] State of Bayes Lecture Series: Session 6 Gaussian Processes

🎙️ Speaker: Maxim Kochurov \| ⏰ Time: 9am PT / 12pm ET / 6pm Berlin

Gaussian Processes are probably the most powerful models you can encounter in Bayesian statistics. To apply them, you first need to get familiar with the basics and first principles. While complicated formulas are awesome, we'll more focus on intuition and possible applications. In this lesson, you'll know

what is a kernel
how to think about kernel parameters
how to make gaussian process hierarchy

And a bonus, we'll lead a coding session where we apply a Gaussian process to analyze unbalanced stratified poll data.

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.

Subscribe to our PyMCLabs YouTube to see past videos.
Feedback Form: https://forms.gle/xHsaVzWrzDxRjhrt5

Sessions (generally bi-weekly) The full course is:

Session 1️⃣: Introduction ▶️ L1: VIDEO
Session 2️⃣: Bayesian Thinking ▶️ L2: VIDEO
Session 3️⃣: Hierarchical modeling ▶️ L3: VIDEO
Session 4️⃣: Interpretable Linear Regressions ▶️ L4: VIDEO
Session 5️⃣: Bayesian AB testing ▶️ L5: VIDEO
Session 6️⃣: Gaussian Processes (22th June, 2023)
Session 7️⃣: Gaussian Processes for Time Series

💼 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.

🔗 Connect with Maxim: 👉 LinkedIn: https://www.linkedin.com/in/ferrine 👉 Twitter: https://twitter.com/ferrine96 👉 GitHub: https://github.com/ferrine 👉 Website: https://ferrine.github.io

📖 Code of Conduct: Please note that participants are expected to abide by PyMC's Code of Conduct.

🔗 Connecting with PyMC Labs: 👥 LinkedIn: https://www.linkedin.com/company/pymc-labs/ 🐦 Twitter: https://twitter.com/pymc_labs 🎥 YouTube: https://www.youtube.com/c/PyMCLabs 🤝 Meetup: https://www.meetup.com/pymc-labs-online-meetup/

🔗 Connecting with PyMC Open Source: 💬 Q&A/Discussion: https://discourse.pymc.io 🐙 GitHub: https://github.com/pymc-devs/pymc 💼 LinkedIn: https://www.linkedin.com/company/pymc/mycompany 🐥 Twitter: https://twitter.com/pymc_devs 📺 YouTube: https://www.youtube.com/c/PyMCDevelopers 🎉 Meetup: https://www.meetup.com/pymc-online-meetup/

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