Build a Recommendation System with the Multi-Armed Bandit Algorithm
Last Updated on June 28, 2023 by Editorial Team
Author(s): Flo
Originally published on Towards AI.
Data exploration, Data exploitation, and Continuous Learning
Top highlight
stuffed animals-tisou, image by @walterwhites on OpenSea
The Multi-Armed Algorithm is a reinforcement learning algorithm used for resource allocation and decision-making. We will explain how the Multi-Armed technique helps to build a recommendation system for an online shop selling stuffed animals.
Concretely, the objective of this algorithm is to start by randomly trying different options (arms), collect data on the result and as it gathers data, it dynamically allocates more resources to the option with the best result.
We will dive into the details to explain how it works through 3 steps:
Data exploration: understand our data and products by experiment.Data exploitation: find… Read the full blog for free on Medium.
Join thousands of data leaders on the AI newsletter. Join over 80,000 subscribers and keep up to date with the latest developments in AI. From research to projects and ideas. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming a sponsor.
Published via Towards AI
Towards AI Academy
We Build Enterprise-Grade AI. We'll Teach You to Master It Too.
15 engineers. 100,000+ students. Towards AI Academy teaches what actually survives production.
Start free — no commitment:
→ 6-Day Agentic AI Engineering Email Guide — one practical lesson per day
→ Agents Architecture Cheatsheet — 3 years of architecture decisions in 6 pages
Our courses:
→ AI Engineering Certification — 90+ lessons from project selection to deployed product. The most comprehensive practical LLM course out there.
→ Agent Engineering Course — Hands on with production agent architectures, memory, routing, and eval frameworks — built from real enterprise engagements.
→ AI for Work — Understand, evaluate, and apply AI for complex work tasks.
Note: Article content contains the views of the contributing authors and not Towards AI.
Related posts
Recent Posts
