HSC Result Predictor using Random Forest Regression to forecast student exam scores based on historical data and performance indicators.
A collection of machine learning models for predicting laptop prices
MediaEval challenge 2019 - to predict the memorability of the Videos
BUDGET : VotingRegressor(XGBoost+LightGBM) * (5 Fold CV) — This model, built for a Kaggle insurance regression competition, preprocesses data by imputing missing values (KNN), cleaning, and engineering new features. Statistical analysis reduces features before encoding and scaling for machine learning
Repository showcasing a collection of diverse regression analysis projects including salary prediction and more.
This Repository contains the implementation of various Classification Algorithms on different different datasets.
A hybrid machine learning framework for river discharge forecasting that combines ensemble regression models with the Arithmetic Optimization Algorithm (AOA) for hyperparameter tuning and next-day flow prediction.
This project investigates ensemble learning techniques, combining multiple models to enhance accuracy and robustness. It covers both basic methods (Max Voting, Averaging, Weighted Averaging) and advanced techniques (Stacking, Blending, Bagging, Boosting), aiming to improve predictive performance by addressing model weaknesses.
Predict the university admission using machine learning
This project aims to predict flight arrival delays using various machine learning algorithms. It involves EDA, feature engineering, and model tuning with XGBoost, LightGBM, CatBoost, SVM, Lasso, Ridge, Decision Tree, and Random Forest Regressors. The goal is to identify the best model for accurate predictions.
Implementation of Voting Classifier and Voting Regressor using Ensemble Learning to improve classification and regression performance through model aggregation.
Machine learning project predicting electricity consumption based on ASHRAE dataset.
Key Stroke Based Essay Examination System
started by analysing and determining the aspects required for tuning of the final ml model. Performed Eda and feature engineering inorder to determine the import parameters of the dataset and to derive more useful features, finally creating a ml model by using various different basic and advanced regression techniques.
PredictGrad is a machine learning project designed to identify engineering students at academic risk by forecasting their future academic performance. The system predicts Semester 3 core subject marks using data from earlier semesters and flags students likely to experience a significant decline in performance.
👩💻Artificial Intelligence Course Projects, University of Tehran
End-to-end ML project: detects ideal flagship smartphones using feature engineering, Voting Regressor price prediction, Google Form survey analysis, Streamlit web app, and Tableau interactive dashboard.
🏡House Price Prediction, Artificial Intelligence course, University of Tehran
Problem Moving from traditional energy plans powered by fossils fuels to unlimited renewable energy subscriptions allows for instant access to clean energy without heavy investment in infrastructure like solar panels, for example. One clean energy source that has been gaining popularity around the world is wind turbines. Turbines are massive str…
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