Thompson Sampling Courses and Certifications

Data Science Decisions in Time: Using Data Effectively

Learn to make optimal decisions using data streams, from simple to complex, covering Wald's model, Thompson sampling, change points, Markov chains, and Markov decision processes for effective data analysis and decision-making.

• Coursera
• 1 day 1 hour 10 minutes
• On-Demand
• Free Online Course (Audit)

Artificial Intelligence for Business + ChatGPT Prize [2024]

4298 ratings at Udemy

Solve Real World Business Problems with AI Solutions implemented in Python. Code templates included.

• Udemy
• 15 hours 8 minutes
• On-Demand
• Paid Course

Serrano.Academy

Probability

Explore Bayes Theorem, Hidden Markov Models, Shannon Entropy, Naive Bayes classifier, Beta distribution, and Thompson sampling in this friendly introduction to key probability concepts.

• YouTube
• 1 hour 30 minutes
• On-Demand
• Free Video

Serrano.Academy

Machine Learning

Comprehensive introduction to key machine learning concepts, algorithms, and applications, covering testing, error metrics, recommendation systems, and various classification methods.

• YouTube
• 3 hours 30 minutes
• On-Demand
• Free Video

Simons Institute

Online Learning and Bandits - Part 2

Explore advanced bandit algorithms, including Exponential Weights, UCB, and Thompson Sampling. Learn design principles and analysis techniques for optimal decision-making in uncertain environments.

• YouTube
• 1 hour 4 minutes
• On-Demand
• Free Video

Paul G. Allen School

2019 ADSI Summer Workshop- Algorithmic Foundations of Learning and Control

Explore advanced techniques in reinforcement learning, focusing on randomized value functions and their applications in exploration strategies for complex decision-making problems.

• YouTube
• 50 minutes
• On-Demand
• Free Video

Paul G. Allen School

Bandits - Kevin Jamieson - University of Washington

Explore bandit algorithms and their applications in machine learning, from drug development to content recommendation, with a focus on regret minimization and stochastic models.

• YouTube
• 1 hour 4 minutes
• On-Demand
• Free Video

Launchpad

Deep Bayesian Bandits - Exploring in Online Personalized Recommendations

Explore online personalized recommendations using Deep Bayesian Bandits. Learn about UCB, Thompson Sampling, and innovative approaches like bootstrapping and dropout methods for effective exploration strategies.

• YouTube
• 29 minutes
• On-Demand
• Free Video

Simons Institute

Stochastic Bandits: Foundations and Current Perspectives

Explore key algorithms for sequential learning in stochastic bandits, including Upper Confidence Bound and Thompson Sampling, and their adaptations for various constraints.

• YouTube
• 1 hour 9 minutes
• On-Demand
• Free Video

Data Science Festival

Advanced Techniques for Online Advertisement Spend Optimization

Explore advanced techniques for optimizing online ad spend using Reinforcement Learning, Bayesian statistics, and Thompson sampling to improve budget allocation and maximize returns.

• YouTube
• 1 hour
• On-Demand
• Free Video

VinAI

Adversarially Robust Stochastic Multi-Armed Bandits

Explore adversarially robust stochastic multi-armed bandits for optimal experimental design. Learn about algorithms balancing fast and robust learning in real-world applications like digital advertising.

• YouTube
• 45 minutes
• On-Demand
• Free Video

Valence Labs

Applying Active Learning in Drug Discovery - There's No Free Lunch, but You Can Get a Discount

Explore active learning applications in drug discovery, from prioritizing molecules for synthesis to virtual screening of large libraries, with insights on machine learning's impact across the process.

• YouTube
• 53 minutes
• On-Demand
• Free Video

MLOps World: Machine Learning in Production

Multi-armed Bandits in Production at Stitch Fix

Explore scaling challenges and solutions for multi-armed bandits in online experimentation, including a new method for efficient, deterministic Thompson sampling at Stitch Fix.

• YouTube
• 40 minutes
• On-Demand
• Free Video

Simons Institute

Adaptive Data Collection via Autoregressive Generation in News Recommendation Systems

Discover how autoregressive models can enhance adaptive data collection and decision-making through Thompson sampling, with applications in news recommendation systems and cold-start problems.

• YouTube
• 45 minutes
• On-Demand
• Free Video

Harvard CMSA

Differentially Private Algorithms for Statistical Estimation Problems

Explore differential privacy algorithms across online learning, causal inference, and imbalanced data analysis, focusing on Thompson sampling, synthetic control, and minority data generation techniques.

• YouTube
• 52 minutes
• On-Demand
• Free Video