A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.

Build a Web App called AI-Powered Heart Disease Risk Assessment App

This repository addresses a common scenario in the field of Machine Learning Engineering

NLP notebooks for classification telegram channel name by post text

🏆2nd solution in web ad CTR predict competition🏆

Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation

TSForecasting: Automated Time Series Forecasting Framework

Legal case retrieval challenge. Solution based on similarity search and learning-to-rank methods

This code demonstrates the use of machine learning to model the multimodal nature of a single cell. Using machine learning to predict RNA from DNA, that is, using chromatin accessibility data to predict the RNA gene expression and to predict surface protein from RNA, that is, using RNA sequence data to predict surface protein levels in a cell

The project contains a CatBoost model that makes predictions according to an uploaded csv file using a flask wrapper.

Classifying which released prisoners in Iowa will return to a life of crime using Next-Gen Gradient Boosted Trees

Python package that predicts the appeal topic, topic group and the executor to process the appeal based on its contents

Supporting code for the paper "Finding Influential Training Samples for Gradient Boosted Decision Trees"

Machine Learning – HSE MMLDS 22/23

MLOps – HSE MMLDS 23/24 [python service for training and inferring Catboost classification model on Iris dataset]

Clustering employee performances to predict resignation likelihood and develop strategies for employee retention

A repository for almost every machine learning algorithms

R package for automation of machine learning, forecasting, model evaluation, and model interpretation