https://github.com/torinriley/acon

A dynamic and adaptive machine learning framework designed for optimization and adaptability across datasets and environments.
https://github.com/torinriley/acon

machine-learning ml

Last synced: 6 months ago
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A dynamic and adaptive machine learning framework designed for optimization and adaptability across datasets and environments.

• Host: GitHub
• URL: https://github.com/torinriley/acon
• Owner: torinriley
• License: mit
• Created: 2024-08-22T02:25:18.000Z (9 months ago)
• Default Branch: main
• Last Pushed: 2024-12-03T16:53:26.000Z (6 months ago)
• Last Synced: 2024-12-03T17:51:09.262Z (6 months ago)
• Topics: machine-learning, ml
• Language: Python
• Homepage: https://pypi.org/project/acon/
• Size: 111 KB
• Stars: 5
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • Contributing: CONTRIBUTING.md
  • License: LICENSE
  • Code of conduct: CODE_OF_CONDUCT.md
  • Security: SECURITY.md

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# ACON - Adaptive Correlation Optimization Networks

ACON is an advanced framework designed to optimize machine learning models by leveraging adaptive correlation techniques. It includes modules for real-time data integration, optimization algorithms, meta-learning, and adaptive loss functions. The goal of ACON is to provide tools that enable dynamic model optimization based on evolving data and performance metrics.

### Features

•	Real-time Data Integration: Efficiently integrates incoming data while maintaining a manageable buffer size.

•	Adaptive Optimization: Implements both traditional and advanced optimization techniques (e.g., SGD, Adam) with adaptive learning rates.

•	Meta-Learning: Applies meta-learning strategies to optimize model parameters based on previous task performance.

•	Adaptive Loss Function: Dynamically switches between loss functions (MSE, MAE, Huber) based on training progress.

### Installation

```bash

pip install acon

```

### Documentation

[API Reference](https://github.com/torinriley/ACON/blob/main/DOCS/API.md)