A basic machine learning project to predict store item demand for the next three months using five years of historical data.

Interpreting wealth distribution via poverty map inference using multimodal data

A comprehensive machine learning pipeline for churn prediction in telecom customers using CatBoost, featuring data preprocessing, exploratory data analysis, feature engineering, and model evaluation.

Precision-driven customer churn analysis using CatBoost for accurate predictions and insightful model evaluation.

Objective of this Web app is to predict the likelihood of cardiovascular disease based on lifestyle factors

To identify lithologies, geoscientists use subsurface data such as wireline logs and petrophysical data. However, this process is often tedious, repetitive, and time-consuming. This project aims to use machine learning techniques to predict lithology from petrophysical logs, which are direct indicators of lithology.

Time Series Analysis and Forecasting for an online store using LSTM and CatBoost Algorithm.

Implemeting Modern Day Boosting algos like LightGBM, XgBoost and Catboost to predict yield of Wild Blueberry, done as part of a Kaggle Competition.

This is my final project that I did at the end of teaching a python course at my university "HSE UNIVERSITY". The dataset was taken from the kaggle site.

This project focuses on predicting house prices in Miami using regression techniques. By exploring and analyzing the data, performing feature selection and scaling, trying out different models, and tuning hyperparameters, we aim to develop an accurate model for predicting house prices.

A flask app that predicts student score based on regression models by deployed on AWS beanstock

Credit Risk Analysis with Machine Learning

Рекомендательная система постов для юзеров, на основе характеристик юзеров и информации об их действиях с ранее опубликованными постами. Учебный проект, собранный при прохождении курса StartML от KarpovCourses.

Application of Machine Learning Models to predict Credit Risk

Application of Machine Learning models to predict Company Bankruptcy

Modified fastapi microservice with scheduled A/B tests of base&enhanced catboost models (microservice based on final project of Start ML course at karpov.courses)

Notes, tutorials, code snippets and templates focused on CatBoost for Machine Learning.

HealthCare Length of Stay predictions with Booster algorithms

Deploying Flight Price Prediction via Microsoft Azure

Flight Price Prediction Model Deployment IN Heroku