saccofrancesco/deepshot

Deepshot is a machine learning model designed to predict NBA game outcomes using advanced team statistics and rolling averages. It combines historical performance trends with contextual game data to deliver highly accurate win predictions (70%)

Language: Jupyter Notebook - Size: 151 MB - Last synced at: 2 days ago - Pushed at: 2 days ago - Stars: 111 - Forks: 15

AliAmini93/Fault-Detection-in-DC-microgrids

Using DIgSILENT, a smart-grid case study was designed for data collection, followed by feature extraction using FFT and DWT. Post-extraction, feature selection. CNN-based and extensive machine learning techniques were then applied for fault detection.

Language: Jupyter Notebook - Size: 20 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 58 - Forks: 3

MohamedMostafa010/ExeRay

ExeRay AI detects malicious Windows executables using ML. Analyzes entropy, imports, and metadata for rapid classification, aiding incident response. Built with Python and scikit-learn.

Language: Python - Size: 2.83 MB - Last synced at: 4 months ago - Pushed at: 4 months ago - Stars: 48 - Forks: 7

Soumilgit/XYZ-Bank-Customer-Churn-Predictor

Modular full-stack ML project leveraging Groq API, Streamlit, Supabase, JSON, SciPy, SciKit-Learn, Plotly & EmailJS, alongside libraries - NumPy, Pandas, Utils, OS, Base64, Re, Pillow & DateTime.

Language: Jupyter Notebook - Size: 13.7 MB - Last synced at: 27 days ago - Pushed at: 27 days ago - Stars: 32 - Forks: 1

amzn/confident-sinkhorn-allocation

Pseudo-labeling for tabular data

Language: Jupyter Notebook - Size: 51.7 MB - Last synced at: 7 months ago - Pushed at: over 1 year ago - Stars: 23 - Forks: 7

Dalageo/ML-TitanicShipwreck

Exploring the World's Most Renowned Shipwreck 🚢

Language: Jupyter Notebook - Size: 990 KB - Last synced at: 3 months ago - Pushed at: 12 months ago - Stars: 12 - Forks: 2

edaaydinea/OP1-Prediction-of-the-Different-Progressive-Levels-of-Alzheimer-s-Disease

This is an optional model development project on a real dataset related to predicting the different progressive levels of Alzheimer’s disease (AD).

Language: Jupyter Notebook - Size: 47.5 MB - Last synced at: 8 months ago - Pushed at: about 3 years ago - Stars: 10 - Forks: 4

aj1365/DeepForest-Wetland-Paper

Here are the codes for the "Deep Forest classifier for wetland mapping using the combination of Sentinel-1 and Sentinel-2 data" paper.

Language: Jupyter Notebook - Size: 70.3 KB - Last synced at: over 2 years ago - Pushed at: over 3 years ago - Stars: 10 - Forks: 1

czaloumi/fire-risk-analysis

Machine Learning in Python to assess fire risk in satellite imagery and environmental conditions.

Language: Jupyter Notebook - Size: 57.9 MB - Last synced at: almost 2 years ago - Pushed at: over 4 years ago - Stars: 10 - Forks: 6

edaaydinea/OP2-Prediction-of-the-Different-Progressive-Levels-of-Alzheimer-s-Disease-with-MRI-data

This is an optional model development project on a real dataset related to predicting the different progressive levels of Alzheimer’s disease (AD) with MRI data.

Language: Jupyter Notebook - Size: 16.9 MB - Last synced at: 8 months ago - Pushed at: about 3 years ago - Stars: 9 - Forks: 1

ashishrana1501/Forest-Fire-Prediction

Algerian Forest Fire Prediction

Language: Jupyter Notebook - Size: 4.01 MB - Last synced at: almost 2 years ago - Pushed at: about 3 years ago - Stars: 9 - Forks: 2

xxl4tomxu98/autoencoder-feature-extraction

Use auto encoder feature extraction to facilitate classification model prediction accuracy using gradient boosting models

Language: Jupyter Notebook - Size: 90.1 MB - Last synced at: over 2 years ago - Pushed at: over 3 years ago - Stars: 9 - Forks: 1

tanishq-ctrl/House-price-prediction-and-visualization

This repository contains code and data for analyzing real estate trends, predicting house prices, estimating time on the market, and building an interactive dashboard for visualization. It is structured to cater to data scientists, real estate analysts, and developers looking to understand property market dynamics.

Language: Jupyter Notebook - Size: 20 MB - Last synced at: 8 months ago - Pushed at: 11 months ago - Stars: 8 - Forks: 0

rochitasundar/Customer-profiling-using-ML-EasyVisa

The aim is to find an optimal ML model (Decision Tree, Random Forest, Bagging or Boosting Classifiers with Hyper-parameter Tuning) to predict visa statuses for work visa applicants to US. This will help decrease the time spent processing applications (currently increasing at a rate of >9% annually) while formulating suitable profile of candidates more likely to have the visa certified.

Language: Jupyter Notebook - Size: 7.68 MB - Last synced at: over 2 years ago - Pushed at: almost 4 years ago - Stars: 6 - Forks: 2

MainakVerse/Adamas-AI

Adamas AI is your smart companion for diamond valuation and knowledge. Using advanced machine learning, we provide accurate price predictions and expert advice.

Language: Jupyter Notebook - Size: 2.71 MB - Last synced at: 7 months ago - Pushed at: 7 months ago - Stars: 5 - Forks: 0

ChaitanyaC22/Fraud_Analytics_Credit_Card_Fraud_Detection

The aim of this project is to predict fraudulent credit card transactions with the help of different machine learning models.

Language: Jupyter Notebook - Size: 67.3 MB - Last synced at: 8 months ago - Pushed at: almost 3 years ago - Stars: 5 - Forks: 2

dipesg/Insurance_Fraud

Webapp that predict whether a claim is a fraudulent or not by asking user to put a csv file as mention in schema.json.

Language: Python - Size: 622 KB - Last synced at: over 2 years ago - Pushed at: over 3 years ago - Stars: 5 - Forks: 0

emykes/Flu_Vaccination_ML

The aim of this study is to predict how likely individuals are to receive their H1N1 flu vaccine. We believe the prediction outputs (model and analysis) of this study will give public health professionals and policy makers, as an end user, a clear understanding of factors associated with low vaccination rates. This in turn, enables end users to systematically act on those features hindering people to get vaccinated.

Language: Jupyter Notebook - Size: 4.92 MB - Last synced at: about 1 year ago - Pushed at: almost 4 years ago - Stars: 5 - Forks: 1

AbhishekGit-hash/Credit-Card-Lead-Prediction

A machine learning model to predict whether a customer will be interested to take up a credit card, based on the customer details and its relationship with the bank.

Language: Jupyter Notebook - Size: 11.3 MB - Last synced at: almost 2 years ago - Pushed at: about 4 years ago - Stars: 5 - Forks: 0

merb92/Tanzanian-Waterpoint-Analysis-and-Classifictation

Predict the operational status of waterpoints to help the Tanzanian Government provide more clean water to its population using a Machine Learning Classifier

Language: Jupyter Notebook - Size: 34.5 MB - Last synced at: almost 3 years ago - Pushed at: almost 5 years ago - Stars: 5 - Forks: 2

WalidAlsafadi/Haqiqa-Arabic-Fake-News-Detector

Production-ready Arabic fake news detection system using state-of-the-art AraBERT and XGBoost models. Achieves over 96% F1-score on 13,750 verified news samples. Includes pre-trained models, full training pipeline, and comprehensive evaluation.

Language: Jupyter Notebook - Size: 49.7 MB - Last synced at: about 1 month ago - Pushed at: about 2 months ago - Stars: 4 - Forks: 0

MachineNeyarning/ClassifiersCommittee

Comitê de Classificadores | Projeto N1

Language: Jupyter Notebook - Size: 5.75 MB - Last synced at: 2 months ago - Pushed at: 2 months ago - Stars: 4 - Forks: 0

santiagocanepa/Insta_Bot

AI-powered Instagram bot for precise gender targeting using XGBoost and OpenAI ADA, with 91% accuracy at just $0.001 per 1000 queries. Automates follows/unfollows from user lists or photo likes, and checks follow-backs with randomized human-like actions. Ideal for influencers and marketers aiming for targeted engagement.

Language: TypeScript - Size: 22.3 MB - Last synced at: 7 months ago - Pushed at: 7 months ago - Stars: 4 - Forks: 0

gvarun20/Machine-learning_Simple_projects

use the data set and run the ipynb file

Language: Jupyter Notebook - Size: 50.1 MB - Last synced at: 12 months ago - Pushed at: 12 months ago - Stars: 4 - Forks: 0

pavankethavath/Microsoft-Classifying-Cybersecurity-Incidents-with-ML

A machine learning pipeline for classifying cybersecurity incidents as True Positive(TP), Benign Positive(BP), or False Positive(FP) using the Microsoft GUIDE dataset. Features advanced preprocessing, XGBoost optimization, SMOTE, SHAP analysis, and deployment-ready models. Tools: Python, scikit-learn, XGBoost, LightGBM, SHAP and imbalanced-learn

Language: Jupyter Notebook - Size: 4.54 MB - Last synced at: 6 months ago - Pushed at: about 1 year ago - Stars: 4 - Forks: 0

Pratik94229/Credit-Card-Default-Prediction-End-to-End-Project

This is an end-to-end project that focuses on predicting credit card default using machine learning techniques. The project includes data validation,data preprocessing, model training, evaluation, and deployment.

Language: Jupyter Notebook - Size: 9.64 MB - Last synced at: over 1 year ago - Pushed at: over 2 years ago - Stars: 4 - Forks: 0

cconsta1/SexEst_Notebooks

Example notebooks to produce the models used in the SexEst web application.

Language: Jupyter Notebook - Size: 581 KB - Last synced at: 8 months ago - Pushed at: about 3 years ago - Stars: 4 - Forks: 0

zahrasalarian/Data-Mining-Playground

This repository contains five mini projects covering several main topics in Data Mining, such as data preprocessing, clustering and classification.

Language: Jupyter Notebook - Size: 3.58 MB - Last synced at: about 2 years ago - Pushed at: over 3 years ago - Stars: 4 - Forks: 0

slrvv/CENTRE

Language: R - Size: 437 MB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 3 - Forks: 3

michplunkett/ucpd-incident-scraper

This repository scrapes the UCPD Daily Incident page at a pre-determined frequency and store the incidents on a generic JSON data-store.

Language: Python - Size: 64 MB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 3 - Forks: 2

IzaacCoding36/Projeto-ONIA

Esse repositório será utilizado para a publicação e desenvolvimento do meu projeto para a Olimpíada Nacional de Inteligência Artificial (ONIA) de 2025.

Language: Python - Size: 1.8 MB - Last synced at: 4 months ago - Pushed at: 4 months ago - Stars: 3 - Forks: 0

itshivams/PDF-Outline-Extractor

PDF Outline Extractor is an end-to-end machine learning pipeline that automatically generates structured outlines (Title, H1–H4 hierarchy) from unstructured PDFs — even those without embedded metadata or tags.

Language: Python - Size: 275 KB - Last synced at: about 2 months ago - Pushed at: 4 months ago - Stars: 3 - Forks: 1

galvinguy2002/Loan-Prediction-

Loan Prediction using machine learning

Language: Jupyter Notebook - Size: 342 KB - Last synced at: over 1 year ago - Pushed at: about 2 years ago - Stars: 3 - Forks: 0

ShivamVadalia/Underwater-Waste-Detection-Using-YoloV8-And-Water-Quality-Assessment

Neural Ocean is a project that addresses the issue of growing underwater waste in oceans and seas. It offers three solutions: YoloV8 Algorithm-based underwater waste detection, a rule-based classifier for aquatic life habitat assessment, and a Machine Learning model for water classification as fit for drinking or irrigation or not fit.

Language: Jupyter Notebook - Size: 21.6 MB - Last synced at: over 2 years ago - Pushed at: over 2 years ago - Stars: 3 - Forks: 1

Darshbhi99/Sensor-Fault-Detection

This Project we take Data of the sensor in brake system used in Heavy Duty Vehicles and Detect whether the System Failure is because of APS or not using Machine Learning Model which can be continuously trained and used for Prediction. I have Created WebApp using FASTAPI and deployed on AWS EC2 as a Docker Image through ECR Repositories

Language: Jupyter Notebook - Size: 2.47 MB - Last synced at: almost 2 years ago - Pushed at: almost 3 years ago - Stars: 3 - Forks: 0

SunilGolden/Tomato-Leaf-Disease-Classifier

Language: Jupyter Notebook - Size: 6.46 MB - Last synced at: over 2 years ago - Pushed at: about 3 years ago - Stars: 3 - Forks: 0

apoorvaKR12695/Mobile-Price-Range-Prediction

Supervised ML- Built a Multi-Class classification model to find the relation between features of a mobile phone(RAM, Internal Memory etc) and its selling price. Model will predict the price range indicating how high the price is.

Language: Jupyter Notebook - Size: 6.83 MB - Last synced at: over 2 years ago - Pushed at: over 3 years ago - Stars: 3 - Forks: 4

akthammomani/Credit_Risk_Classification

Classification Modeling: Probability of Default

Language: Jupyter Notebook - Size: 10.3 MB - Last synced at: over 2 years ago - Pushed at: almost 4 years ago - Stars: 3 - Forks: 1

swarnava-96/Rainfall-Prediction

A Flask web app which predicts whether it will rain tomorrow or not.

Language: Jupyter Notebook - Size: 17.7 MB - Last synced at: 5 months ago - Pushed at: over 4 years ago - Stars: 3 - Forks: 0

mandar196/Hate_Speech_Detection-NLP

Created Hate speech detection model using Count Vectorizer & XGBoost Classifier with an Accuracy upto 0.9471, which can be used to predict tweets which are hate or non-hate.

Language: Jupyter Notebook - Size: 27.3 KB - Last synced at: over 2 years ago - Pushed at: about 5 years ago - Stars: 3 - Forks: 3

s0nya23/Loan-Approval-Prediction

When it comes to deciding whether the applicant’s profile is relevant to be granted with loan or not,banks have to look after many aspects. Predicting loan approval is a common application of machine learning in the financial industry.

Language: Jupyter Notebook - Size: 418 KB - Last synced at: 16 days ago - Pushed at: 16 days ago - Stars: 2 - Forks: 1

TejusK123/AutoDeep

Simple downstream stratification of miRDeep2 outputs via XGBoost

Language: Python - Size: 6.04 MB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 2 - Forks: 0

Prinaka/Algo-Trading-Automation

This project is an end-to-end algorithmic trading signal generator that uses technical indicators and a machine learning classifier (XGBoost) to identify buy and sell opportunities for selected stocks.

Language: Python - Size: 171 KB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 2 - Forks: 0

intelligent-life-paradox/ETF-Forecasting-and-Clustering

Trabalho final da disciplina de Aprendizagem de Máquina

Language: Jupyter Notebook - Size: 51.4 MB - Last synced at: 4 months ago - Pushed at: 4 months ago - Stars: 2 - Forks: 1

ESMAaN/Amazon_Product_Reviews

Amazon Product Reviews: Sentiment Analysis with NLP

Language: Jupyter Notebook - Size: 956 KB - Last synced at: 5 months ago - Pushed at: 5 months ago - Stars: 2 - Forks: 0

Arorms/TrafficClassification

2025 ISCC比赛 恶意流量分类

Language: Jupyter Notebook - Size: 21.8 MB - Last synced at: 5 months ago - Pushed at: 7 months ago - Stars: 2 - Forks: 0

DarkMattrMaestro/stats-tmnf-quarto

Un rapport statistique à but d'analyser la relation entre l’étiquette et le cheminement de circuits dans TMNF utilisant la classification

Language: TeX - Size: 31 MB - Last synced at: 7 months ago - Pushed at: 7 months ago - Stars: 2 - Forks: 0

pregismond/northstar-snowparkml-modeling

Predicting Food Truck Locations Using Snowpark ML and XGBoost

Language: Jupyter Notebook - Size: 2.94 MB - Last synced at: 4 months ago - Pushed at: 10 months ago - Stars: 2 - Forks: 1

TomerYS/Medical-Data-Classifier

ML model for Kaggle competition: TAU Intro2DS - Final Assignment - Spring 2023

Language: Python - Size: 1.18 GB - Last synced at: 7 months ago - Pushed at: 10 months ago - Stars: 2 - Forks: 0

SimranS22/Heart-Disease-Prediction-Model-SurTech

A ML application(deployed on flask) to detect heart disease in patients based on medical features.

Language: Jupyter Notebook - Size: 8.26 MB - Last synced at: 11 months ago - Pushed at: 11 months ago - Stars: 2 - Forks: 1

SeyedMuhammadHosseinMousavi/PSO-Fuzzy-XGBoost-Classifier-Boosted-with-Neural-Gas-Features-on-EEG-Signals-in-Emotion-Recognition

PSO Fuzzy XGBoost Classifier Boosted with Neural Gas Features on EEG Signals in Emotion Recognition

Language: Python - Size: 1.13 MB - Last synced at: 12 months ago - Pushed at: 12 months ago - Stars: 2 - Forks: 0

moayadeldin/DiaLoop

Android/iOS app for Diabetes monitoring and prediction. (UI-based features & Predictive Analysis using Deep Learning)

Language: Dart - Size: 2.94 MB - Last synced at: 12 months ago - Pushed at: 12 months ago - Stars: 2 - Forks: 0

RuiFSP/mlzoomcamp2024-midterm-project

Midterm project for mlzoomcamp 2024

Language: Jupyter Notebook - Size: 43.1 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 2 - Forks: 0

tderick/android-malware-detection

This project aims to build an effective classification model to classify a mobile application as Benign or Malware. To do so, we'll evaluate multiple classification models using different metrics and select the best model with better performance for our dataset. Finally, we deployed our model as a REST API using FastAPI.

Language: Jupyter Notebook - Size: 5.55 MB - Last synced at: 3 months ago - Pushed at: about 1 year ago - Stars: 2 - Forks: 1

cego669/DatathonEngopeVI

Equipe: Embrapeiros. Solução proposta para o Datathon do VI ENGOPE (Encontro Goiano de Probabilidade e Estatística). Obs: FOMOS CAMPEÕES!!!!!!!!

Language: Jupyter Notebook - Size: 3.43 MB - Last synced at: 4 months ago - Pushed at: about 1 year ago - Stars: 2 - Forks: 1

AbhinavSharma07/Fraud_Analytics-Credit_Card_Fraud_Detection

The aim of this project is to predict fraudulent credit card transactions with the help of different machine learning models.

Language: Jupyter Notebook - Size: 3.39 MB - Last synced at: about 2 months ago - Pushed at: over 1 year ago - Stars: 2 - Forks: 0

oladimeji-kazeem/bank-customer-churn-predictor

Customer churn is a critical issue for banks, as retaining customers is more cost-effective than acquiring new ones. This project aims to analyse customer churn in a bank and develop a predictive model to identify customers who are likely to leave, and the responsible factors.

Language: Python - Size: 5.25 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 2 - Forks: 1

Nishant2018/classification-with-nlp-xgboost-and-pipelines

Natural Language Processing (NLP) is a field of artificial intelligence that focuses on the interaction between computers and humans through natural language.

Language: Jupyter Notebook - Size: 24.4 KB - Last synced at: 9 months ago - Pushed at: over 1 year ago - Stars: 2 - Forks: 0

Nishant2018/Academic-Success-Classification-XGBoost-

XGBoost is an open-source machine learning library that provides efficient and scalable implementations of gradient boosting algorithms. It is known for its speed, performance, and accuracy, making it one of the most popular and widely-used machine learning libraries in the data science community.

Language: Jupyter Notebook - Size: 7.03 MB - Last synced at: 6 months ago - Pushed at: over 1 year ago - Stars: 2 - Forks: 0

StrangeCoder1729/FinancialFraudDetectionModels

Developed and evaluated machine learning and deep learning models for detecting financial fraud.

Language: Jupyter Notebook - Size: 2.58 MB - Last synced at: 12 months ago - Pushed at: over 1 year ago - Stars: 2 - Forks: 1

karthik-d/FungiCLEF-2022-using-Network-Ensembles

Scripts, figures and working notes for the participation in FungiCLEF-2022, part of the 13th CLEF Conference, 2022

Language: Python - Size: 15.5 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 2 - Forks: 2

SINGHxTUSHAR/Credit-Card-Fraud-Detection

Credit-Card-Fraud-Detection project is a binary classification project which predicts the Fraud by using the different classification algorithms

Language: Jupyter Notebook - Size: 2.75 MB - Last synced at: 7 months ago - Pushed at: over 1 year ago - Stars: 2 - Forks: 0

grknc/Customer-Churn-Analyzer-with-ML

Telco Churn Analysis and Modeling is a comprehensive project focused on understanding and predicting customer churn in the telecommunications industry. Utilizing advanced data analysis and machine learning techniques, this project aims to provide insights into customer behavior and help develop effective strategies for customer

Language: Jupyter Notebook - Size: 3.09 MB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 2 - Forks: 0

nicolaivicol/ml-pred-default-deploy-aws-sagemaker

Modelling and prediction of default + deployment via AWS Sagemaker

Language: HTML - Size: 10.3 MB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 2 - Forks: 0

keerthikkn/Aviation_delay_prediction

flight delay prediction using XGboost classifier

Language: Jupyter Notebook - Size: 4.99 MB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 2 - Forks: 0

LuluW8071/Twitter-Fake-Profile-Detection

Machine learning models for identifying real-time fake profiles on Twitter

Language: Jupyter Notebook - Size: 603 KB - Last synced at: 9 months ago - Pushed at: about 2 years ago - Stars: 2 - Forks: 0

Siddharth1989/LearnerCentricFeedbackEnhancement

Developing a feedback theory-informed natural language processing (NLP) model to enable large-scale evaluation of written feedback, and analysing a large set of feedback extracted from Moodle using this model to understand the presence of student-centred feedback elements, the commonality and differences in feedback provision across disciplines.

Language: Jupyter Notebook - Size: 5.22 MB - Last synced at: over 2 years ago - Pushed at: over 2 years ago - Stars: 2 - Forks: 0

Billie-LS/Trading_ML_Algo_Experimentation

Variety of Jupyter Lab files examining different ML code for trading using yFinance

Language: Jupyter Notebook - Size: 1.01 MB - Last synced at: over 2 years ago - Pushed at: over 2 years ago - Stars: 2 - Forks: 0

santurini/Heart-Rate-Zones-Prediction

The aim of this work was to predict the heart rate zones. To do this we applied several data transformation techniques which we then used to pull an Xgboost model.

Language: Jupyter Notebook - Size: 55.7 KB - Last synced at: over 2 years ago - Pushed at: almost 3 years ago - Stars: 2 - Forks: 0

parulsharma098/Cardiovascular-Risk-Prediction

This Project is based upon a CHDs (Cardiovascular Heart Diseases) research dataset which has over 3000 records and 16 attributes. Since, the target variable belongs to Categorical attribute, We built classification models for the future predictions of CHDs in patients considering the features.

Language: Jupyter Notebook - Size: 9.09 MB - Last synced at: over 2 years ago - Pushed at: about 3 years ago - Stars: 2 - Forks: 0

mohammadtavakoli78/Data-Mining

This is projects of Data Mining

Language: Jupyter Notebook - Size: 7.93 MB - Last synced at: over 2 years ago - Pushed at: over 3 years ago - Stars: 2 - Forks: 1

hedzd/AUT-Datamining-projects

Projects and practical assignments for data mining course at AUT, spring 2022. Projects contain main topics in data mining, such as data preprocessing, clustering, classification and assosiation rules.

Language: Jupyter Notebook - Size: 3.22 MB - Last synced at: over 2 years ago - Pushed at: over 3 years ago - Stars: 2 - Forks: 0

Sidessh/Multi-Class-Multi-Output-Classification

Multi - Output Multi-Class Classification problem, Job-Type, and Job-Category Prediction

Language: Jupyter Notebook - Size: 22.9 MB - Last synced at: over 2 years ago - Pushed at: over 3 years ago - Stars: 2 - Forks: 1

abduliante/vehicle-default-loan-prediction

Forecasting the likelihood of a customer defaulting their auto loan using classification models

Language: Python - Size: 69.7 MB - Last synced at: about 1 month ago - Pushed at: almost 4 years ago - Stars: 2 - Forks: 1

hanaecarrie/CS5228_kaggle_income50K_classification

CS5228 Kaggle Inclass Competition: Predicting if Income > 50K

Language: Jupyter Notebook - Size: 130 MB - Last synced at: almost 3 years ago - Pushed at: almost 5 years ago - Stars: 2 - Forks: 1

AdityaShinde716/Diabetes-Prediction

Developed a robust diabetes prediction system with rigorous preprocessing, feature engineering, and optimized ML models. Implemented efficient training and evaluation workflows to ensure high accuracy, reliability, and clear interpretability—demonstrating strong applied machine-learning expertise.

Language: Jupyter Notebook - Size: 2.56 MB - Last synced at: about 22 hours ago - Pushed at: 3 days ago - Stars: 1 - Forks: 0

shubh-iiit/MPCE-Prediction-Pipeline

This repository contains code and resources for predicting Monthly Per Capita Expenditure (MPCE) using machine learning models, with a focus on sector (rural/urban) and income class stratification. The project includes data preparation, model training, evaluation, and a frontend for user interaction.

Language: Jupyter Notebook - Size: 32.1 MB - Last synced at: 1 day ago - Pushed at: 3 days ago - Stars: 1 - Forks: 0

HarshitWaldia/LoanSenseAI

This project identifies high-risk borrowers to help reduce NPAs, improve credit decisions, and strengthen financial stability. Evaluated using AUC-ROC, as required by the challenge.

Language: Jupyter Notebook - Size: 12.3 MB - Last synced at: 13 days ago - Pushed at: 13 days ago - Stars: 1 - Forks: 0

ANSHAM1/SentinelAI_Nids

a custom, ML-powered network intrusion detection system

Language: Rust - Size: 2.39 MB - Last synced at: 15 days ago - Pushed at: 15 days ago - Stars: 1 - Forks: 0

ScrPzz/rongowai-earth-surface-classifier

Land/Water binary classifier based on Delay Doppler Map data from Rongowai

Language: Jupyter Notebook - Size: 70 MB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 1 - Forks: 0

iiasa/ggcm-feature-importance

Feature attribution pipeline for Global Gridded Crop Model (GGCM) simulations

Language: Python - Size: 61.5 KB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 1 - Forks: 0

Awais-Asghar/SkinSense-Multi-Model-Skin-Cancer-Classifier

A machine learning project for binary classification of skin cancer as malignant or benign, utilizing models like XGBoost, LGBM Classifier, Adaboost, SVM, and Logistic Regression. Features comprehensive data preprocessing, model training, and evaluation for accurate diagnosis.

Language: Jupyter Notebook - Size: 8.56 MB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 1 - Forks: 0

SermetPekin/spml2

spml2-mltools is a convenient package for applying machine learning workflows with a Streamlit app, generating Excel outputs, and visualizations.

Language: Python - Size: 384 KB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 1 - Forks: 0

XingYihang1/Customer_churn_prediction_using_a_novel_meta-classifier

论文复现项目：基于Oracle元分类器的客户流失预测，复现相关论文研究成果，通过集成决策树、随机森林、XGBoost等多种机器学习算法，采用SelectKBest+GridSearchCV和Permutation Features Selection+BayesSearchCV两种特征选择和超参数优化策略增加基分类器池，实现堆叠集成和动态选择集成并提高Oracle元分类器的理论上限。

Language: Python - Size: 5.44 MB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 1 - Forks: 0

herrerovir/Steel-fault-classifier

A machine learning classification project aimed to predict faults on industrial steel plates.

Language: Jupyter Notebook - Size: 6.66 MB - Last synced at: 2 months ago - Pushed at: 2 months ago - Stars: 1 - Forks: 0

SebastianGranadosJ/Orthopedic-Anomaly-Detection-MlModel

Binary classification of orthopedic anomalies using XGBoost and hyperparameter tuning with Optuna.

Language: Jupyter Notebook - Size: 628 KB - Last synced at: 2 months ago - Pushed at: 2 months ago - Stars: 1 - Forks: 0

Vaishnavi-vi/Classify_spotify_audio_genre_-

A machine learning project for automatic music genre classification using extracted audio features. The project compares multiple models — Logistic Regression, Decision Tree, Random Forest,XGBoost and ANN — and includes an interactive Streamlit app for real-time genre prediction.

Language: Jupyter Notebook - Size: 6.35 MB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 1 - Forks: 0

gabiircode/TechChallenge2

Projeto de Data Analytics para prever a tendência diária do índice IBOVESPA (alta/baixa) utilizando dados históricos.

Language: Jupyter Notebook - Size: 196 KB - Last synced at: 4 months ago - Pushed at: 4 months ago - Stars: 1 - Forks: 0

SaketJha-323/Liver_Cirrhosis_Stage_Detection_System

Liver Cirrhosis Stage Detection System Using Random Forest and XGBoost with Stacking Classifier

Language: Jupyter Notebook - Size: 13.9 MB - Last synced at: 5 months ago - Pushed at: 5 months ago - Stars: 1 - Forks: 0

Naddour98/my-1st-project

My 1st data analysis project - Predicting Employee Turnover using ML models

Language: Jupyter Notebook - Size: 16.2 MB - Last synced at: 6 months ago - Pushed at: 6 months ago - Stars: 1 - Forks: 0

jibbs1703/Classic-ML-Models

This repository contains scripts for developing, training and evaluating machine learning models using several python frameworks.

Language: Jupyter Notebook - Size: 3.31 MB - Last synced at: about 2 months ago - Pushed at: 6 months ago - Stars: 1 - Forks: 0

dpb24/fake-news-detector

📰 NLP: Fake News Detection using Classical Machine Learning

Language: Jupyter Notebook - Size: 2 MB - Last synced at: 6 months ago - Pushed at: 6 months ago - Stars: 1 - Forks: 0

KKeshav1101/mini_project

A Django Application Interface for Hate Speech Detection Mini Project

Language: Python - Size: 334 KB - Last synced at: 6 months ago - Pushed at: 6 months ago - Stars: 1 - Forks: 1

Onome-Joseph/Customer-Churn-Prediction

This project predicts whether a customer is likely to stop patronizing a business by making use of historical customer data.

Language: Jupyter Notebook - Size: 1.53 MB - Last synced at: about 1 month ago - Pushed at: 6 months ago - Stars: 1 - Forks: 0

mahnoorsheikh16/Sketchify-A-Quick-Draw-drawing-classifier

Implementation of a sketch‐recognition pipeline inspired by Google’s Quick, Draw!. Includes data preprocessing and feature‐engineering scripts, three Bayesian classifiers alongside Logistic Regression, SVM, K-NN and XGBoost baselines, and an RNN model.

Language: Jupyter Notebook - Size: 7.8 MB - Last synced at: 4 months ago - Pushed at: 7 months ago - Stars: 1 - Forks: 0

aadhamashraf/Fraud-Detection-Interpretability-and-Explainability

Developing fraud detection systems using a variety of machine learning and deep learning models. Emphasis is placed on model explainability to ensure transparency in predictions, an essential aspect in financial applications.

Language: Jupyter Notebook - Size: 24.3 MB - Last synced at: 7 months ago - Pushed at: 7 months ago - Stars: 1 - Forks: 0

mahnoorsheikh16/Credit-Card-Default-Prediction

This project focuses on predicting whether a customer will default on their credit card payment in the upcoming month. Utilizing historical transaction data and customer demographics, the project employs various machine learning algorithms to distinguish between risky and non-risky customers for better credit risk management.

Language: Jupyter Notebook - Size: 14.6 MB - Last synced at: 7 months ago - Pushed at: 7 months ago - Stars: 1 - Forks: 0

UsmanShaikh24/Machine-Learning-Model-For-Anomaly-Detection-and-Predictive-Maintenance

This project addresses the growing need for intelligent industrial maintenance systems. By applying machine learning techniques, we aim to detect anomalies in machine behavior, predict machine failures, estimate Remaining Useful Life (RUL), and schedule maintenance tasks based on priority—enhancing reliability and minimizing downtime.

Language: Jupyter Notebook - Size: 6.19 MB - Last synced at: 7 months ago - Pushed at: 7 months ago - Stars: 1 - Forks: 0

Ramtin-Karbaschi/Titanic_XGBOOSTmodel

XGBoost classification model predicting Titanic passenger survival with data preprocessing, feature engineering, and SMOTE for class balancing. Developed for the Kaggle Titanic competition.

Language: Jupyter Notebook - Size: 9.77 KB - Last synced at: 7 months ago - Pushed at: 7 months ago - Stars: 1 - Forks: 0

CaritoRamos/predictive-classification-model-in-r

Predicting hotel booking cancellations using Machine Learning in R, with data preprocessing and model training. Random Forest achieved 85.23% accuracy, highlighting lead time and previous cancellations as key factors.

Language: HTML - Size: 1.86 MB - Last synced at: 5 months ago - Pushed at: 8 months ago - Stars: 1 - Forks: 0