Vyacheslav EfimovinTowards Data ScienceReinforcement Learning, Part 5: Temporal-Difference LearningIntelligently synergizing dynamic programming and Monte Carlo algorithmsJul 131Jul 131
Vyacheslav EfimovinTowards Data ScienceSystem Design: Load BalancerOrchestrating strategies for optimal workload distribution in microservice applicationsJun 281Jun 281
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
Vyacheslav EfimovinTowards Data ScienceSystem Design: Quadtrees & GeoHashEfficient geodata management for optimized search in real-world applicationsMay 83May 83
Vyacheslav EfimovinTowards Data ScienceReinforcement Learning, Part 2: Policy Evaluation and ImprovementFrom data to decisions: maximizing rewards with policy improvement methods for optimal strategiesApr 232Apr 232
Vyacheslav EfimovinTowards Data ScienceReinforcement Learning, Part 1: Introduction and Main ConceptsMaking the first step into the world of reinforcement learningApr 91Apr 91
Vyacheslav EfimovinTowards Data ScienceSystem Design: Bloom FilterSmartly transforming a hash table to a probabilistic data structure to trade accuracy for large memory gainsMar 243Mar 243
Vyacheslav EfimovinTowards Data ScienceSystem Design: Consistent HashingUnlocking the power of efficient data partitioning in distributed databases like Cassandra and Dynamo DB.Mar 13Mar 13
Vyacheslav EfimovinTowards Data ScienceQuestion-Answering Systems: Overview of Main ArchitecturesDiscover design approaches for building a scalable information retrieval systemFeb 281Feb 281