Vyacheslav EfimovinTowards Data ScienceReinforcement Learning, Part 8: Feature State ConstructionEnhancing linear methods by smartly incorporating state features into the learning objective3d ago3d ago
Vyacheslav EfimovinTowards Data ScienceIntuitive Explanation of Async / Await in JavaScriptDesigning asynchronous pipelines for efficient data processingSep 8Sep 8
Vyacheslav EfimovinTowards Data ScienceReinforcement Learning, Part 7: Introduction to Value-Function ApproximationScaling reinforcement learning from tabular methods to large spacesAug 221Aug 221
Vyacheslav EfimovI Have Hit the Gym for 50 Consecutive Days — Here is What I Think About ItIt is not only about building muscles — amazing benefits I analyzed after 50 days of gym commitmentAug 18Aug 18
Vyacheslav EfimovinTowards Data ScienceReinforcement Learning, Part 6: n-step BootstrappingPushing the boundaries: generalizing temporal difference algorithmsAug 7Aug 7
Vyacheslav EfimovHow to Deal with Rejections in LifeDiscover a smart strategy to control emotions against rejectionsJul 269Jul 269
Vyacheslav EfimovinTowards Data ScienceReinforcement Learning, Part 5: Temporal-Difference LearningIntelligently synergizing dynamic programming and Monte Carlo algorithmsJul 132Jul 132
Vyacheslav EfimovinTowards Data ScienceSystem Design: Load BalancerOrchestrating strategies for optimal workload distribution in microservice applicationsJun 282Jun 282
Vyacheslav EfimovinTowards Data ScienceReinforcement Learning, Part 4: Monte Carlo ControlHarnessing Monte Carlo algorithms to discover the best strategiesJun 111Jun 111
Vyacheslav EfimovinTowards Data ScienceReinforcement Learning, Part 3: Monte Carlo MethodsFrom casinos to AI: unveiling the power of Monte Carlo methods in complex environmentsMay 23May 23