34j/lightgbm-callbacks

A collection of LightGBM callbacks. (DART early stopping, tqdm progress bar)

Language: Python - Size: 448 KB - Last synced: 3 days ago - Pushed: 3 days ago - Stars: 2 - Forks: 0

princessEmilyy/ML-project-diabetes-

Project for applied classical ML course at the Weizmann institute

Language: Python - Size: 183 MB - Last synced: 11 days ago - Pushed: 11 days ago - Stars: 0 - Forks: 0

cmunch1/nba-prediction

A project to deploy an online app that predicts the win probability for each NBA game every day. Demonstrates end-to-end Machine Learning deployment.

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sofi211/Portfolio

Проекты, написанные за время обучения в Яндекс Практикум

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10027BC/bigcontest10027

This project aims to predict the win rate, hitting average and ERA of 10 KBO teams in the 2020 season. The hitting average and ERA was predicted through a LSTM model and the win rate was predicted through a LGBM model.

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himanshu-03/Spaceship-Titanic-Kaggle-Competition

The task is to predict whether a passenger was transported to an alternate dimension during the Spaceship Titanic's collision with the spacetime anomaly. To help us make these predictions, we are given a set of personal records recovered from the ship's damaged computer system.

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Nicolas-Bolouri/LGBM-Solution-Amex-Kaggle

LGBM Solution to AMEX Default Prediction Kaggle Competition

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brunodifranco/project-rossmann-sales

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

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brunodifranco/project-insuricare-ranking

Insuricare project - Creating a customer ranking system

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yashksaini-coder/Multi-Class-Prediction-of-Obesity-Risk

Multi-Class Obesity Risk Prediction Project | Prediction of obesity risk in individuals using various factors, which is related to cardiovascular disease.

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smnomaan/amex_default_prediction

Apply machine learning algorithms to predict credit default by leveraging an industrial scale dataset

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taher-software/Optiver-Realized-Volatility-Prediction

In financial markets, volatility captures the amount of fluctuation in prices. For trading firms like Optiver, accurately predicting volatility is essential for the trading of options, whose price is directly related to the volatility of the underlying product.In this Kaggle competition,we had built models that predict short-term volatility for hundreds of stocks across different sectors. Our models will be evaluated against real market data collected in the three-month evaluation period after training.

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taher-software/Riiid-Answer-Correctness-Prediction

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 .

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taher-software/Jane-Street-Market-Prediction

In this project, Jane Street which is a quantitative trading company ,challenged us to build our own quantitative trading model to maximize returns using market data from a major global stock exchange. Next, they’ll test the predictiveness of our models against future market returns.

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sabitendu/Capstone-Project-On-Appliance_Energy_Prediction

Using Machine Learning Regression Algorithms, Predicting the Energy Used by the Appliance.

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The1enin/Yandex_practicum

Here you can see my projects that I completed as part of my studies

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TomerRonen34/treeboost_autograd

Easy Custom Losses for Tree Boosters using Pytorch

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maxtiandi/training_projects

Сборник всех выполненных учебных проектов курса Яндекс.Практикум "Специалист по Data Science".

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teamoptimusai/datstorm-initial-round 📦

This repo is Dedicated to the Initial Round of DataStorm Competition held on Kaggle Platform. We got the 3rd place in the initial round.

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jodiambra/Breast-Cancer-Predictions

Web application that can be used to predict breast cancer, based on cell features. Model classifies result as benign or malignant.

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rtaiello/big-data-taxi-fare-amount

BigData: The goal is to be able to create a model capable of predicting the taxi fare in New York.

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AndreMenezesDS/PA004_health_insurance

Health Insurance Cross-Sell(Learning to Rank Machine Learning Project)

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yashksaini-coder/Bank-Loan-Default

Objective is to develop a predictive model for a consumer finance company to identify potential loan defaulters. By analyzing historical loan data, & diff. data the factors that influences loan default rate.

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parv-bhargava/RateMe

A Web application that estimates your app's rating in google play store based on the features you decide

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PathofData/LGBM_C_inference

A project that demonstrates the use of the lgbm C++ API to perform inference without any python dependencies.

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wavyrai/London-Housing-Model

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

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raphaelmss92/Classificacao-Fake-News

Repositório com notebooks do projeto final da especialização em Inteligencia Artificial e Machine Learning na PUC-Minas

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amirhosseinamerimanesh/Load-Forecasting-Machine-Learing

This repository is for load forecasting using machine learning.

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spiritysdx/CPGMCM_2023_Code

2023 全国研究生数学建模竞赛 代码仓库 E 题 出血性脑卒中预后预测_集成静态模型和时序模型

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mztrk/LGBMModelling

Fit - train - test binary LGBM Model

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vaitybharati/XGBM-and-LGBM

XGBM-and-LGBM

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shreyash2610/Machinehack-Mathcothon-Car-Price-Prediction

With the rise in the variety of cars with differentiated capabilities and features such as model, production year, category, brand, fuel type, engine volume, mileage, cylinders, colour, airbags and many more, we are bringing a car price prediction challenge for all. We all aspire to own a car within budget with the best features available. To solve the price problem we have created a dataset of 19237 for the training dataset and 8245 for the test dataset.

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YigitTurali/LGBM_MA

An implementation of a novel Gradient Boosting algorithm inspired by ARMA models, as detailed in the associated IEEE paper on nonlinear sequential regression.

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sauravmishra1710/Heart-Failure-Condition-And-Survival-Analysis

Perform a survival analysis based on the time-to-event (death event) for the subjects. Compare machine learning models to assess the likelihood of a death by heart failure condition. This can be used to help hospitals in assessing the severity of patients with cardiovascular diseases and heart failure condition.

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Denis-Mukhanov/Chicago_taxi_trips_BigData

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Denis-Mukhanov/toxic-comments

Yandex Practicum Data Science project

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DongChanKIM2/AI-Data-Hackathon-Competiton

Agricultural Video AI Data Utilization Idea Hackathon

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DongChanKIM2/BC-Financial-Data-Contest

BC Card Financial Big Data Contest

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adzinota/data_scientist_yandex_course

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

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jvicentem/kaggle_malware_microsoft_8th

Microsoft Malware Prediction Challenge. 8th position solution.

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dmitryamel/portfolio

A vault with some of projects done by me

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mnokno/VectorBorneDiseasePrediction

Vector borne disease prediction based on patient symptoms using an ensemble of CatBoots, XGBoost and LGBM.

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hrsht-13/OxyMeter

Language: Python - Size: 2.82 MB - Last synced: 10 months ago - Pushed: almost 3 years ago - Stars: 0 - Forks: 1

toniesteves/enem-2016

Previsão da nota de matemática dos alunos participantes do ENEM 2016.

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john-fante/gamma-hadron-separation-xgb-lgbm-svm

The main goal of the project is to distinguish gamma-ray events from hadronic background events in order to identify and study celestial gamma-ray sources accurately.

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prathyyyyy/Microsoft-Malware-Prediction

Malware prediction implemented by effective data visualization and manipulation techniques done with Python, sweetviz,plotly, scikit-learn and LGBM

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Yassaadi/bank_scoring

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Pradyothsp/backorder-prediction

This is a Django web application that uses machine learning to predict whether a product will go on backorder or not. It uses a pre-trained Random Forest Classifier, Decision Tree and LGBM models to make predictions based on various features such as product availability, lead time, and more.

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mnokno/CrabAgePrediction

Crab age predication from its characteristics using ensemble of tree based models.

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aaaastark/Intrusion-Detection-System

Attack Detection, Parameter Optimization and Performance Analysis in Enterprise Networks (ML Networks) for Intrusion Detection System IDS.

Size: 454 KB - Last synced: 7 months ago - Pushed: 7 months ago - Stars: 5 - Forks: 1

pypye/WiDS_Datathon_2023_solution

WiDS Datathon 2023 Contest 13th place WiDS Global and 1st place WiDS Hanoi solution by UET 杨蓉 Team (Binh Nguyen Thai, Duc Tran Van, Duong Tran Thuy, Dung Tran Thuy)

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mnokno/WildBlueberryYieldPrediction

Wild blueberry yield prediction using ensemble of LightGBM and CatBoost.

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mnokno/BinaryPulsarStarClassification

Binary classification of start as pulsar or non- pulsar based on observation results using CatBoost, XGBoost and LGBM.

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mnokno/ConcreteStrengthPrediction

Concrete strength prediction based on its composition and curing process using CatBoost, XGBoost and LGBM.

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mnokno/WineQualityPrediction

Wine quality prediction based on the amount of various chemicals present in wine. Using two different methods, ANN and LGBM.

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Anjali-DA/Introduction-of-Machine-Learning

🏵️Getting started with Machine Learning🤖| ML algorithms📔| skitlearn| Prediction of new datasets from Kaggle📉

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EgorovYuriy/Yandex.Practicum_Data_Science_Projects

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fintech-quagga-group/american-express-default-prediction

Machine learning solutions for the American Express credit default prediction Kaggle competition

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vladimir-abramov/data_science_projects

Yandex Praktikum Data Science Projects

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lordtt13/WeHack-2.0

Problem Statement 1 Prediction Model foe Wehack2.0, trying to find defects.

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mayb333/cars_price_prediction

This represents the car's price predictor based on LightGBM + Optuna. The final goal is to use it to predict my father's car price.

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nancyhamdan/WiDS-2022

Predicting building energy consumption as part of the WiDS 2022 Datathon

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UtkarshKharche29/Youtube-Adview-Prediction

I worked on this Live project while working as a Machine Learning Intern at Internship Studio that was offered by National Engineering Olympiad 5.0

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SubeyteT/Supermarket_App_BI-Analytics

LGBM and logistic regression for prediction of customers' second time transaction for an online market app.

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matheusventurads/health-insurance-cross-sell

Cross Sell Prediction for Health Insurance Company.

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minerva-ml/open-solution-gstore 📦

Open solution to Kaggle's: Google Analytics Customer Revenue Prediction :bar_chart:

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cremerf/SentimentAnalysisMoviesStanford

NLP project. Sentiment Analysis on movies reviews from Stanford dataset. Used BoW, IT-IDF and LightGBM (ran with GPU RTX3060)

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pinouche/ubiquant_kaggle

code for the Ubiquant market prediction Kaggle competition. Top 1% rank: 20th out of 2893 teams.

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sidharth178/Youtube-Adview-Prediction

A Machine Learning project for Machine Learning Internship offered by InternshipStudio.

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ilymak7/zindi_competitions

This repo contains my work on zindi competitions

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bcaitech1/p4-dkt-no_caffeine_no_gain

No-Caffeine-No-Gain's Deep Knowledge Tracing (DKT)

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iDolphin99/Argricultural_price_predict

농산물 데이터 분석을 통한 가격 예측 AI model별 비교

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rprkh/Music-Genre-Recommender

Music Genre Recommender website that can identify and recommend 10 different genres of music using Light Gradient Boosting Machine (LGBM). An accuracy of 90% was achieved on the test set by tuning the hyperparameters of the model with Optuna.

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uzunb/house-prices-prediction-LGBM

This repo has been developed for the Istanbul Data Science Bootcamp, organized in cooperation with İBB and Kodluyoruz. Prediction for house prices was developed using the Kaggle House Prices - Advanced Regression Techniques competition dataset.

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grigorevmp/G-Research-Crypto-Forecasting

Pack of Kaggle notebooks for Kaggle competition

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RachanaJayaram/MalwarePrediction

Using machine learning models to predict the probability of a windows system getting infected by various families of malware, based on different properties of that system.

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RoccoJay/Audio_to_Emotion

Classifying Audio to Emotion

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oguzerdo/machine-learning-algorithms

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

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SatishGollu/CryptoCurrency_prediction

University project

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DorMiz43/ML_case_study

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malort/Stacked_Models_Telecom_Churn

Language: Jupyter Notebook - Size: 412 KB - Last synced: 12 months ago - Pushed: almost 2 years ago - Stars: 0 - Forks: 0

hassan-ademola/Washington-Housing-Prices-Predictions

A machine learning project that explores and predicts the prices of houses in Washington, USA

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Ducanger/Fake-News-Detection

Vietnamese Fake News Detection Based on Hybrid Transfer Learning Model and TF-IDF

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geangohn/Bayesian-Optimization

My own realization of Bayesian Optimization for LightGBM

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samirhinojosa/OC-P7-implement-a-scoring-model

Implement a Scoring Model

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SenSudi/EE-695-Applied-Machine-Learning

Implemented various ML algorithms with and without library functions. Final Project-->Application of LGBM, XGBoost, Catboost and SVC

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rachit-shah/pubg-player-placement-prediction

Kaggle Competition PUBG Player Placement Prediction (ALDA Project Group P09)

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will-fong/instacart_online_grocery_shopping_analysis

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.

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AyanPahari/Kaggle--Taxi-Fare-Prediction

The aim of this project is to work on a (completed) Kaggle challenge on taxi fare prediction.

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PIETRO-ing/fraud_detection

fraud detection and anomaly detection on credit card transactions

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izzypatrick21/car-price-prediction

Used car price prediction with linear, lasso and LGBM regression algorithm

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mahdi-robbani/lsda

Large Scale Data Analysis at University of Copenhagen (KU) 2020

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oasidorshin/RaifHack2021

RaifHack2021 32/377 solution

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brpy/ashrae-energy-prediction

A kaggle case study to predict energy consumption.

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Toukenize/grab_aiforsea_safety

Submission for Grab Challenge - AI For Sea 2019

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isra-st/Customer_Segmentation

Explorartory Data Analysis with visualization. Use the supervised machine learning models to predict the customer segmentation. Use unsupervised learning model K Nearest Neighbors to create new clusters. Create Personas of the new clusters.

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madimedia/credit_score_data_modeling

Data analysis, preprocessing and custom ML model implementation for a credit score app.

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brendanartley/riiid_education_lgb_model

LGBM predicting wether a student will get their next question right or wrong.

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kamliolfa1/AI-hack-Tunisia-2019-Tunisian-Fraud-Detection-Challenge

The AI Hack Tunisia 2019 is the biggest ML/AI Hackathon ever in Tunisia, Africa, and the Middle East North Africa (MENA) region. It takes place on 20-22 September. The event is a double hackathon: the first part is an individual Machine Learning Challenge, and the second part is a group (or as we like to say, startup) competition focused on a specific technology. With mentors, judges, and competitors from all over the world, it’s going to be a blast!

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rs-anderson/Zindi-Hackathon-Winning-Solution

The Algebras' (Shane Weisz and Ryan Anderson) winning solution for the "UCT Datathon: The Ultimate Hacking Challenge", hosted by Zindi

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