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Description of  Contextual MultiArmed Bandit Problems in Python

Published 3/2024 Created by Hadi Aghazadeh MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 70 Lectures ( 9h 0m ) | Size: 2.9 GB All you need to master and apply multi-armed bandit problems into real-world problems What you'll learn: Master all essential Bandit Algorithms Learn How to Apply Bandit Problems into Real-world Applications with Focus on Product Recommendation Learn How to Implement All Essential Aspects of Bandit Algorithms in Python Build Different Deterministic and Stochastic Environments for Bandit Problems to Simulate Different Scenarios Learn and Apply Bayesian Inference for Bandit Problems and Beyond as a Byproduct of This Course Understand Essential Concepts in Contextual Bandit Problems Apply Contextual Bandit Problems in a Real-World Product Recommendation Dataset and Scenario Requirements: No obligational pre-requisites Description: Who this course is for: Web Application Developers Researchers working on Action optimization Machine Learning Developers and Data Scientists Startup Enthusiasts Driven to Develop Customized Recommendation Apps.