InTowards AIbyMuhammad Abiodun SULAIMAN·Aug 13Engineering a Multi-Agent AI Platform — Part 2: The BanditThis is Part 2 of a series on engineering AI systems that learn in production. Part 1 introduced the complexity classifier and three…
InAnalyst’s cornerbyDr Swarnendu AI·Jun 22Thompson sampling aka Explore vs ExploitTwo Buttons, Unknown Which Is Better. How a Machine Decides Which to Show You — By Rolling Dice Loaded With Its Own Beliefs.A response icon2A response icon2
Shraddha Rao·Jun 6I tried to rebuild X’s algorithm. Here’s what actually happened.Not a summary. Not a tutorial. Just what it was like to build this thing.
Eric Picot Ds·Oct 17, 2025When ‘penne pasta’ beats ‘Pinsa dough’: the story of an algorithm that listens to its customersWhat you’ll discover in this article:
Jayarabihay·Oct 2, 2025Día 30 de 100 días de aprendizaje y creación de proyectos de Machine Learning: Reinforcement…Vamos a un nuevo modelo de Reinforcement Learning aplicado al anterior dataset que es el Thompson Sampling: es un método probabilístico…
QuarkAndCode·Sep 28, 2025Best Practices for Bandits: A Multi‑Armed Bandit Guide for A/B TestingLearn when to use multi armed bandits vs A/B tests, plus practical tips on Thompson Sampling, UCB, sticky bucketing, update cadence, and…
Tanmay Joshi·Aug 9, 2025How I Built an AI System That Learns Where to Spend Marketing DollarsThe $500 Question That Started Everything
Reeti Pandey·Jul 28, 2025Bayesian Modeling, Part 2: From Theory to Real-World DecisionsIntroduction: The Power of Bayesian Thinking in Practice
InVanguard TechbyVanguard Tech·Jun 5, 2025Smarter web wins: A/B testing vs. multi-armed bandits unpackedA/B testing and multi-armed bandits are transforming web optimization. Discover which method fits your goals to achieve better results.
Hang Nguyen·Feb 28, 2025Machine learning 101 P19: Thompson samplingWe have previously gone through the MAB problem in part 18 with one of bandit algorithms: UCB. We will go through another algorithm that…
