Find a project you can actually build
Working IoT, AI/ML and embedded builds with abstracts, component lists, documentation, and developer support — ready for your final-year submission.
Deep Learning-Based Pneumonia Detection from Chest X-Rays
This project develops pneumonia detection from chest x-rays using a GAN-based generative architecture trained on an appropriate image/video/audio/text dataset. The trained network is optimized for inference speed and served through a real-time demo application.
Image Captioning using CNN-LSTM Architecture
This project develops image captioning using a ResNet/EfficientNet backbone trained on an appropriate image/video/audio/text dataset. The trained network is optimized for inference speed and served through a real-time demo application.
Movie Box Office Revenue Predictor using ML
This project builds a data-driven pipeline for movie box office revenue predictor using Decision Trees and Random Forest trained on historical/tabular data. The final model is wrapped in an interactive dashboard so non-technical users can get predictions and insights instantly.
Employee Attendance Anomaly Detection using ML
This project builds a data-driven pipeline for employee attendance anomaly detection using Random Forest and XGBoost trained on historical/tabular data. The final model is wrapped in an interactive dashboard so non-technical users can get predictions and insights instantly.
Customer Complaint Category Classifier using ML
This project builds a data-driven pipeline for customer complaint category classifier using Logistic Regression and SVM trained on historical/tabular data. The final model is wrapped in an interactive dashboard so non-technical users can get predictions and insights instantly.
Cab Fare Prediction System using ML Regression
This project builds a data-driven pipeline for cab fare prediction system regression using Random Forest and XGBoost trained on historical/tabular data. The final model is wrapped in an interactive dashboard so non-technical users can get predictions and insights instantly.
Fraudulent Transaction Pattern Detector using ML
This project builds a data-driven pipeline for fraudulent transaction pattern detector using regression models (Linear, Ridge, Lasso) trained on historical/tabular data. The final model is wrapped in an interactive dashboard so non-technical users can get predictions and insights instantly.
Employee Resignation Risk Predictor using ML
This project builds a data-driven pipeline for employee resignation risk predictor using ensemble stacking of multiple classifiers trained on historical/tabular data. The final model is wrapped in an interactive dashboard so non-technical users can get predictions and insights instantly.
Customer Purchase Behavior Prediction using ML
This project builds a data-driven pipeline for customer purchase behavior prediction using Logistic Regression and SVM trained on historical/tabular data. The final model is wrapped in an interactive dashboard so non-technical users can get predictions and insights instantly.
Exam Result Prediction & Risk Flagging System using ML
This project builds a data-driven pipeline for exam result prediction & risk flagging system using K-Means and hierarchical clustering trained on historical/tabular data. The final model is wrapped in an interactive dashboard so non-technical users can get predictions and insights instantly.
Restaurant Rating Prediction using ML
This project builds a data-driven pipeline for restaurant rating prediction using Logistic Regression and SVM trained on historical/tabular data. The final model is wrapped in an interactive dashboard so non-technical users can get predictions and insights instantly.
Energy Consumption Forecasting using ML
This project builds a data-driven pipeline for energy consumption forecasting using Decision Trees and Random Forest trained on historical/tabular data. The final model is wrapped in an interactive dashboard so non-technical users can get predictions and insights instantly.