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🚀 NeuralDelphi - Fast, Easy Machine Learning
A high-performance, pure Delphi machine learning framework. No Python. No external DLLs. Just fast, native code.
✨ Features
- 🚀 Arena-Based Memory — Zero allocation/deallocation during training
- ⚡ SIMD Assembly — AVX-512 and SSE kernels with CPUID auto-detection
- 🔄 Automatic Differentiation — Full autograd with computation graphs
- 🧵 Thread Pool Parallelization — Efficient multi-core utilization
- 📦 Zero Dependencies — Pure Delphi, compiles standalone
- 🎛️ N-Dimensional Tensors — Full Shape/Strides support for any dimensionality
- 📡 Broadcasting — NumPy-style automatic shape broadcasting
- 🔢 Batch Operations — Efficient handling of multiple data points
🚀 Getting Started
To use NeuralDelphi, follow these steps. The process is simple and requires no coding skills.
1. Visit the Download Page
Go to the following link to access the download options:
2. Download the Application
On the release page, you will see a list of available files. Look for the most recent release. Click on the file that matches your system.
3. Install NeuralDelphi
Once the download is complete:
- Locate the downloaded file, usually in your “Downloads” folder.
- Double-click the file to run the installer.
Follow the on-screen instructions to complete the setup.
4. Start Using NeuralDelphi
After installation, find the NeuralDelphi application in your Start Menu or Desktop. Double-click to open the application and begin your machine learning journey.
🔧 System Requirements
NeuralDelphi runs on Windows systems. Ensure your device meets the following requirements:
- Operating System: Windows 10 or later
- RAM: At least 4 GB (8 GB or more recommended)
- Disk Space: 100 MB available for installation
📖 Usage Instructions
Once NeuralDelphi is installed, you can start using it right away. Here are some basic actions you can perform:
1. Load Your Data
Use the import features to load your data. Your data can be in various formats. Ensure your data is clean and prepared for best results.
2. Set Up Your Model
Use the user-friendly interface to choose your model options. Some options might include choosing parameters or algorithms suited for your data type.
3. Run Your Training
Once your model is set, start the training process by clicking the appropriate button. Monitor the training process through the interface.
4. View Results
After training, view your results using the built-in tools. Analyze the output and adjust your model as needed for better performance.
💬 Support
If you encounter any issues or have questions, there are resources available:
- Documentation: Comprehensive user guides and tutorials are available on the repository.
- Community Forum: Join discussions and seek help from fellow users.
For further assistance, please submit an issue on the GitHub repository.
🔗 Additional Resources
For advanced features, tips, and updates:
This guide will help you smoothly navigate through downloading and using NeuralDelphi. Enjoy exploring the capabilities of this machine learning framework!