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Crop Recommendation System based on Soil Data using ML
This project builds a data-driven pipeline for crop recommendation system based on soil data 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.
GAN-Based Image Super Resolution System
This project develops gan-based image super resolution system 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.
Loan Approval Prediction using Ensemble ML
This project builds a data-driven pipeline for loan approval prediction 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.
Deep Learning-Based Face Mask Detection System
This project develops face mask detection system using a YOLO-based real-time detector 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.
Real-Time Object Detection using YOLO for Surveillance
This project develops real-time object detection using a Convolutional Neural Network (CNN) 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.
Neural Style Transfer Application for Image Art
This project develops neural style transfer application for image art using a CNN-LSTM hybrid 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.
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.
Video Action Recognition using 3D-CNN
This project develops video action recognition using a Convolutional Neural Network (CNN) 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.
Deep Learning-Based License Plate Recognition System
This project develops license plate recognition system using a 3D-CNN for spatio-temporal data 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.
Customer Segmentation for Targeted Marketing using ML
This project builds a data-driven pipeline for customer segmentation for targeted marketing using Gradient Boosting (LightGBM/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.
Deep Learning-Based Medical Tumor Detection from Scans
This project develops medical tumor detection from scans using an LSTM/GRU sequence model 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.