Alexandre Andorra

📢 Exciting news! Join us for a new Learning Bayesian Statistics Modeling Webinar!

🌟 Transform Your Approach to Data Science with Fast & Efficient Gaussian Processes 🌟

🗓️ Date: April 18, 2024

⏰ Time: 4:00pm (16:00)

🌍 Timezone: UTC-3

📚 Introduction: Dive into the cutting-edge world of data analysis and modeling in our upcoming webinar, where we demystify the revolutionary Hilbert Space Gaussian Process (HSGP) approximation.

This technique is your key to leveraging Gaussian processes at an unprecedented scale, transforming complex data into actionable insights.

🔍 What You Will Learn:

• Foundational Concepts Simplified: Begin your journey with an accessible introduction to Gaussian processes and the principles of spectral analysis methods. We break down complex ideas into understandable concepts, ensuring you grasp the fundamentals of HSGP approximation.

• Real-World Application: Through the lens of the seminal Birthdays dataset, witness the power of HSGP in action. We'll guide you step-by-step, demonstrating how this method can be applied to tangible data challenges, making the abstract concrete.

• Innovative Techniques Explained: At the heart of HSGP lies the Laplacian's spectral decomposition—its eigenvalues and eigenvectors. Learn how a truncated sum of eigenvectors, combined in a linear fashion, can approximate the kernel of a Gaussian process with high efficiency. Discover how the selection of coefficients, influenced by the spectral density of the Gaussian process kernel, unlocks faster computations without sacrificing precision.

• Speed and Efficiency: Uncover the game-changing observation that the eigenvectors used in HSGP approximation remain constant across different hyperparameters of the Gaussian process kernel. This insight is crucial for accelerating computational processes, enabling you to handle larger datasets more efficiently than ever before.

🌟 Why Attend?

Don't miss this unique opportunity to enhance your machine learning and modeling expertise. Gain a comprehensive understanding of Gaussian Processes through the innovative lens of HSGP approximation.

Whether you're a data science enthusiast, a seasoned analyst, or a professional looking to refine your skill set, this webinar will equip you with the knowledge and tools to elevate your analytical capabilities.

✨ Join us and step into the future of data analysis. Expand your skills, unlock new possibilities, and gain a competitive edge with the HSGP approximation. ✨

🎙️ Our guest speaker, Juan Orduz, is a mathematician (Ph.D., Humboldt Universität Berlin) and data scientist. He is interested in interdisciplinary applications of mathematical methods, particularly time series analysis, Bayesian methods, and causal inference.

🎟️ Limited spots available! Register now to secure your seat, and don't miss your chance to interact live with our speakers. If you're a Patron of the Learning Bayesian Statistics podcast, you can submit questions in advance.

🎁 As a bonus, patrons will enjoy early access to the webinar recordings.

👥 Feel free to invite your friends and colleagues to this open webinar. Spread the word and let's learn together! 🤝 Just share them the Topmate registration link.

Can't wait to see you there! Best Bayesian wishes 🖖

Useful references

• Slides of the presentation
• HSGP intro notebook
• Watch previous modeling webinars
• Juan's webiste
• Juan on GitHub
• Juan on Twitter
• Juan on Linkedin
• Juan on Mastodon
• Buy Juan a coffee
• Follow Learning Bayesian Statistics
• Support the show on Patreon
• Alex on Twitter
• Alex on LinkedIn
• 1:1 Mentorship with Alex
• Bayes stats online courses