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Discover a comprehensive approach to constructing credit risk models. We employ various machine learning algorithms like LightGBM and CatBoost, alongside ensemble techniques for robust predictions. Our pipeline emphasizes data integrity, feature relevance, and model stability, crucial elements in credit risk assessment.
Replication package containing code and experimental results related to a Euro-Par 2023 paper titled: Pure C++ Approach to Optimized Parallel Traversal of Regular Data Structures
A performant and memory efficient storage for immutable strings with C++17. Supports all standard char types: char, wchar_t, char16_t, char32_t and C++20's char8_t.
An extension of micro mouse on WEBOTS using the flood filled algorithm, A star, Dijkstra’s and Breadth first search algorithm for moving the E-puck robot from start to goal in an NxM sized maze whose map was unknown to the robot (mapping and path planning). Further, leveraged Error Correction for accurate turning and recursive Backtracking algor…