Gaussian Processes Courses and Certifications

MITCBMM

Learning What We Know and Knowing What We Learn - Gaussian Process Priors for Neural Data Analysis

Explore Gaussian process priors for neural data analysis, covering latent variable models, Bayesian inference, covariance kernels, and factor analysis. Gain insights into advanced techniques for understanding complex neural datasets.

• YouTube
• 1 hour 31 minutes
• On-Demand
• Free Online Course

Richard McElreath

Statistical Rethinking 2022 - Gaussian Processes

Explore Gaussian processes, spatial confounding, and phylogenetic inference in statistical modeling. Learn to apply these concepts to real-world examples like oceanic covariance and primate phylogeny.

• YouTube
• 1 hour 25 minutes
• On-Demand
• Free Online Course

Richard McElreath

Statistical Rethinking 2023 - Gaussian Processes

Explore Gaussian processes and their applications in statistical analysis, including oceanic spatial confounds and phylogenetic regression, for advanced data modeling techniques.

• YouTube
• 1 hour 22 minutes
• On-Demand
• Free Online Course

Alan Turing Institute

Some Thoughts on Gaussian Processes for Emulation of Deterministic Computer Models

Explore Gaussian Process emulators for complex computer models in uncertainty quantification, focusing on theoretical aspects and applications to climate, tsunami, and earthquake problems.

• YouTube
• 54 minutes
• On-Demand
• Free Online Course

Introduction to Scientific Machine Learning

Learn the basics of machine learning with hands-on practical examples on engineering applications.

• edX
• 16 weeks, 6-7 hours a week
• On-Demand
• Free Online Course (Audit)

METUopencouseware

Signals and Systems II

Comprehensive exploration of advanced signal processing concepts, including probability theory, random variables, stochastic processes, and spectral analysis for electrical engineering applications.

• YouTube
• 1 day 8 hours
• On-Demand
• Free Online Course

Machine Learning 1 - 2020

Comprehensive introduction to machine learning fundamentals, covering probability theory, regression, classification, neural networks, clustering, and advanced topics like kernels and Gaussian processes.

• YouTube
• 21 hours
• On-Demand
• Free Online Course

Open Data Science

Making Robust Business Decisions with Sparse Data - Sarah Jarvis, PhD | ODSC Europe 2019

Explore data-efficient solutions for supply chain management, focusing on forecasting with limited data and making robust decisions in complex, dynamic systems.

• YouTube
• 44 minutes
• On-Demand
• Free Online Course

Simons Institute

Computation in Very Wide Neural Networks

Explore infinite-width neural networks, their correspondence to Gaussian processes, and implications for deep learning performance and dynamics in parameter space.

• YouTube
• 49 minutes
• On-Demand
• Free Online Course

Abhishek Thakur

Hyperparameter Optimization - This Tutorial Is All You Need

Explore various hyperparameter optimization techniques including Grid Search, Random Search, Bayesian Optimization, Hyperopt, and Optuna to fine-tune models and optimize functions effectively.

• YouTube
• 1 hour
• On-Demand
• Free Online Course

Association for Computing Machinery (ACM)

Algorithms for Heavy-Tailed Statistics - Regression, Covariance Estimation, and Beyond

Explore advanced statistical techniques for handling heavy-tailed data, including regression and covariance estimation, with a focus on SOS assumptions and median of means framework.

• YouTube
• 20 minutes
• On-Demand
• Free Online Course

Alan Turing Institute

The Automatic Statistician - Professor Zoubin Ghahramani

Explore Bayesian model selection strategies for automated data analysis and report generation, with insights on regression models, Gaussian processes, and computational resource allocation.

• YouTube
• 55 minutes
• On-Demand
• Free Online Course

Institute for Pure & Applied Mathematics (IPAM)

Uncertainty Quantification of Quantum Chemical Methods - IPAM at UCLA

Explore uncertainty quantification in quantum chemistry, covering error estimation, benchmarking, and machine learning approaches for improved accuracy in computational methods.

• YouTube
• 42 minutes
• On-Demand
• Free Online Course

Institute for Pure & Applied Mathematics (IPAM)

Methods for Scalable Probabilistic Inference - IPAM at UCLA

Explore scalable probabilistic inference methods for astrophysics, focusing on Gaussian Processes for time series analysis and open-source tools to accelerate Bayesian inference with large datasets.

• YouTube
• 46 minutes
• On-Demand
• Free Online Course

Institute for Pure & Applied Mathematics (IPAM)

Learning-Based Model Predictive Control - Towards Safe Learning in Control

Explores integrating learning techniques with optimization-based control for safe, high-performance systems. Discusses methods for data-driven modeling, safety filters, and constraint satisfaction in robotics applications.

• YouTube
• 51 minutes
• On-Demand
• Free Online Course