Show HN: Autograd.c – a tiny ML framework built from scratch (github.com)

A developer has introduced Autograd.c, a lightweight machine learning framework built entirely from scratch, showcasing its capabilities on 'Show HN'. This initiative aims to offer a simplified yet functional alternative to more complex frameworks like PyTorch, emphasizing a closer interaction with hardware—referred to as "tiny torch, but close to metal." Autograd.c is designed to be user-friendly while retaining essential features, making it particularly appealing to developers and researchers interested in deep learning without the overhead of larger libraries. The significance of Autograd.c lies in its potential to foster a deeper understanding of machine learning fundamentals by allowing users to directly engage with the underlying architecture. The framework supports basic functionalities like loading datasets (for instance, the CIFAR-10), model creation, and training processes. Initial results from training show average losses and accuracy metrics that suggest Autograd.c is capable of handling the complexities of model training, albeit with room for improvement. This venture could encourage innovation and experimentation within the AI/ML community, particularly among those seeking a more granular approach to model development and training.