Introduction to simpleAI
simpleAI is a powerful C++17 library designed for building deep neural networks from scratch. It emphasizes high efficiency and vectorized implementations, leveraging OpenMP for parallel processing. This library is ideal for developers and researchers looking to implement neural networks without relying on heavy frameworks, providing a lightweight and customizable solution for machine learning tasks.
Key Features:
- C++17 Implementation: Utilizes modern C++ features for better performance and maintainability.
- Deep Neural Networks: Supports various architectures for building complex models.
- OpenMP Optimization: Enhances performance through parallel processing, making it suitable for large datasets.
- Customizable: Allows users to modify and extend functionalities as per their requirements.
Use Cases:
- Research: Ideal for academic research in machine learning and artificial intelligence.
- Prototyping: Quickly prototype neural network models without the overhead of larger frameworks.
- Performance-Critical Applications: Suitable for applications where performance is a key concern, such as real-time data processing.