Parkinson's Disease Detection Using Deep Learning|Machinelearning|Best IEEE Machine Learning Project
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🎥 Parkinson's Disease Detection Using Deep Learning and CNN | Web App Demo 🎥
Welcome to our latest video where we showcase an innovative project on Parkinson's disease detection using deep learning and convolutional neural networks (CNN). In this video, we walk you through the entire process of creating a web application that can detect Parkinson's disease based on a user's spiral drawing.
Here's what you'll find in this video:
Dataset Collection: Learn how we gathered and prepared our dataset.
Data Augmentation & Preprocessing: See the techniques we used to enhance and clean our data.
Model Training: Discover how we trained our model using transfer learning and CNN, achieving an impressive training accuracy of 100%.
Testing & Validation: Watch our model's performance during testing, where we reached an accuracy of 98-99%.
Web App Integration: We demonstrate how users can upload their spiral drawings to our web app to get an instant prediction.
🔍 Key Features:
Comprehensive walkthrough of our machine learning pipeline.
High accuracy rates in detecting Parkinson's disease.
User-friendly web application interface.
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Thank you for watching, and we hope you enjoy the video!
Referred Papers are :
1.https://ieeexplore.ieee.org/document/...
2. https://ieeexplore.ieee.org/document/...
#ParkinsonsDisease #DeepLearning #CNN #MachineLearning #WebApp #AI #TechProjects
