Multi Armed Bandit

This blog post is a collaboration with Genesis AI Labs, we are working towards revolutionising independent research and applied machine learning for real-word industrial solutions. This article is one of several from our “AI Agents Research Pod.” Hope you have fun In this post, I am very excited to share…

Sam Cohan, Principal Machine Learning Engineer at Udemy Introduction This is Part II of a two-part blog post about how we built a multi-armed bandit (MAB) system for recommendation and ranking use cases at Udemy. In Part I, we covered the theoretical and practical data science details for such a system…

Introduction In recent years, multi-armed bandits (MAB) have been enjoying a surge in popularity as explore-exploit balancing approaches continue to show success in a wide variety of applications. One particularly successful application has been the use of multi-armed bandits for recommendations. Introducing exploration into the recommendation approach helps address common recommendations…

An Introduction to Multi-Armed Bandits Problem — Should I stay or should I go? The multi-arm bandit problem is a problem that has its place in probability theory, machine learning, and reinforcement learning concepts. In this problem, we have limited resources and an event where we will use these resources and various alternative options, and our goal…

Primary authors: Vijay Yadav, Deepak HR Co-author : Narasimha 1. INTRODUCTION MakeMyTrip has multiple ranking/recommendation systems. We use learning to rank, sequence-based recommendation models, content or behavior representation-based algorithms, and collaborative filtering algorithms too. After the customer browses around, searching for hotels in city A, B or C, a substantial portion search…

A powerful and easy way to apply reinforcement learning. — Reinforcement learning is an interesting field which is growing and achieving great performance in gaming, robotics and at the financial market. A nice thing is that you don’t have to start with Deep Q-Learning agents! For some problems, it’s enough to implement a simple algorithm based on the principles of…

Multi Armed Bandit (MAB) made easy and applications — This is an intuitive primer to Multi Armed Bandit algorithm. This is not technical. There will be as little math as possible. You are walking in the street and you find a coin on the ground. The question is: “How do I know if the coin is fair or not…

Artificial intelligence is where a machine learns to decide and take actions intelligently. Unsupervised learning finds patterns in the underlying data. Supervised learning predicts the target variable based on input variables. However, they don’t really tell us which action to take. They can’t take actions without any further optimization strategy…

You find yourself on the floor of a dusty, old timey casino holding a $100 bill. Spread out in a long row in front of you are twenty slot machines. All of these machines have a different house edge. In the long run, some will take your money, while others…