Placement prediction using machine learning is a technique that analyzes data from past student placements to forecast future job prospects. It uses factors like grades, skills, and experience to estimate the likelihood of a student getting hired. This helps students and institutions better prepare for the job market.

CLASSIFICATION model to predict whether a customer will carry out a bank transaction Uses: Holdalt, Cross validation, Random Forest, Neural Network

Purchase Prediction Model for an Advertising Campaign on a Social Network - Own Project Capstone HarvardX 125.9

Data Mining sur le dataset Bank Marketing UCI - EDA, classification, prédiction de souscription à un dépôt à terme

Sistema ML para predicción de tiempos de entrega usando Random Forest (R²=0.802). Incluye pipeline completo, API REST, dashboard Streamlit con integración LLM y análisis SQL.

This work presents an AI-driven approach to automating the task prioritization process, addressing new real-world challenges such as reducing subjectivity and adapting to changing requirements.

S&P 500 equity selection system (20.2% return, 0.93 Sharpe) using Random Forest. End-to-end backtesting pipeline.

An Insurance company that has provided Health Insurance to its customers wants to building a model to predict whether the customers will also be interested in Vehicle Insurance provided by the company.

Doctor Fee Prediction" is a GitHub repository that scrapes data on doctors from Practo using Beautifulsoup and creates a table with details such as specialties, years of experience, and consultation fees.

IotchulindraRai/Heart-disease-prediction-using-Ml-project with GUI

AQI Predictor V2 use multiple Supervised Machine Learning with Hyper tuning. ML algorithms used Linear Regressor, Lasso Regressor, Decision Tree Regressor, Random Forest Regressor, XGboost Regressor. The Model deployed on web and can predict AQI visit https://aqipredictor.up.railway.app/

End-to-end Python machine learning pipeline using Scikit-Learn and Random Forest to predict NFL Draft outcomes. Features advanced EDA, automated missing value imputation, Label Encoding, hypothesis-driven feature engineering (BMI), and grid search hyperparameter optimization evaluated via 5-Fold Stratified Cross-Validation ROC-AUC.

Investment Analysis and Asset Mgmt, Time Series Analysis & Forecasting, Machine Learning in Finance & Causal Inference Methods

Este repositório contém a solução para um desafio de classificação, onde foram treinados e otimizados modelos KNN e Random Forest para predizer se um cômodo está ocupado ou desocupado.

Predictive models on data: fraud detection

Machine learning project predicting mortgage default risk using classification models and model comparison.

Collating important concepts:

A production level modular data science project aims to predict generous tippers for taxi drivers.

Previsão de Preços de Aluguel no Airbnb usando Machine Learning

Machine learning algorithms implemented from scratch using only NumPy. Each one includes a demo and math walkthrough so you can understand how they actually work.