© 2024 Hopping Mad Games, LLC. All Rights Reserved.
This software and all associated documentation, code, concepts, implementations, and intellectual property are the exclusive property of Hopping Mad Games, LLC.
READ THIS CAREFULLY BEFORE VIEWING, DOWNLOADING, OR USING THIS CODE:
- ❌ NOT OPEN SOURCE - This code is NOT released under any open-source license
- ❌ NO COMMERCIAL USE - Commercial use is strictly prohibited without written permission
- ❌ NO REDISTRIBUTION - You may not distribute, copy, or share this code
- ❌ NO MODIFICATIONS - Creating derivative works is prohibited
- ❌ NO REVERSE ENGINEERING - Reverse engineering or extraction of concepts is prohibited
This repository contains a portfolio demonstration project showcasing technical capabilities. It is provided solely for:
- ✅ Portfolio review and evaluation purposes
- ✅ Demonstration of technical skills and implementation approaches
- ✅ Educational viewing of coding techniques and patterns
Any use beyond viewing for evaluation purposes requires explicit written permission from Hopping Mad Games, LLC. This includes but is not limited to:
- Commercial deployment or integration
- Using code snippets in other projects
- Adapting concepts or implementations
- Teaching or training based on this code
- Competitive analysis or benchmarking
This is an advanced web application showcasing:
- Browser-Based Machine Learning: Full CNN training with TensorFlow.js
- WebGPU/WebGL Acceleration: Optimized GPU computation in browsers
- Web Worker Background Processing: Uninterrupted training when tab is backgrounded
- Real-time Visualization: Live training progress, loss curves, and feature maps
- Advanced UI/UX: Responsive design with collapsible sections and tabbed interface
- Camera Integration: Real-time image capture and processing
- Session Management: Complete state persistence and restoration
- Advanced Backend Selection: Automatic WebGPU > WebGL > CPU prioritization
- Message Passing Architecture: Sophisticated Web Worker communication
- Tensor Memory Management: Proper disposal and lifecycle management
- Error Handling: Comprehensive fallback strategies
- Performance Optimization: Multi-threaded training with responsive UI
- Type Safety: Full TypeScript implementation with strict typing
View the demonstration at: https://tashaskyup.github.io/simple-ml-demo-1/
Note: The live demo is provided for evaluation purposes only and is subject to the same licensing restrictions as the source code.
For licensing inquiries, commercial use permissions, or collaboration opportunities:
Hopping Mad Games, LLC Contact information available upon request for legitimate business inquiries
This repository is provided "AS IS" for demonstration purposes only. Hopping Mad Games, LLC makes no warranties regarding functionality, performance, or suitability for any purpose.
Unauthorized use of this proprietary software may result in legal action.
By accessing this repository, you acknowledge that you have read, understood, and agree to be bound by these terms.
© 2024 Hopping Mad Games, LLC - All Rights Reserved