Solution for Kaggle "IEEE-CIS-Fraud-Detection" competition (top 26%)

Analytics Vidhya Jantahack Agriculture, Hackathon.

Australia rain prediction model with LGBM

Учебные проекты (Яндекс.Практикум)

Instacart’s data science team plays a big part in providing this delightful shopping experience. Currently they use transactional data to develop models that predict which products a user will buy again, try for the first time, or add to their cart next during a session.

This repo contains machine learning algorithms such as Linear, Logistic Regression, Random Forests, XGBoost, LGBM

Predicting Rossmann sales six weeks in advance. Feel free to access the Telegram Bot in the link below.

This contains all the machine learning projects.

Bank Customer Churn Prediction using Ensemble Model

This repository contains the code to build a prediction engine for London housing prices

농산물 데이터 분석을 통한 가격 예측 AI model별 비교

Проекты, выполненные на курсе "Специалист по Data Science" в Яндекс.Практикум

A retail chain wants a 3-month demand forecast for 10 different stores and 50 different products.

Repository for the "Google Analytics Customer Revenue Prediction" Kaggle competition.

Predicting building energy consumption as part of the WiDS 2022 Datathon

Practicum Workshop

Kaggle competition, which challenge us to create algorithms for "Knowledge Tracing," the modeling of student knowledge over time. The goal is to accurately predict how students will perform on future interactions. We had pair our machine learning skills using Riiid’s EdNet data to get an AUC of 0.738 in private leaderboard .

Code for my first ML competition on kaggle. The two codes are LSTM and LGBM prediction model with technical analysis features. To download dataset for the competition visit : https://www.kaggle.com/competitions/jpx-tokyo-stock-exchange-prediction

Implement a Scoring Model