Perpetual ML

About the application Perpetual ML

Perpetual ML is a groundbreaking technology that empowers businesses by accelerating model training by more than 100x. This is achieved by eliminating the time-consuming hyperparameter optimization step, opening doors to limitless possibilities for applications across diverse industries.

Background and Development

Perpetual ML is the result of extensive research and development aimed at enhancing the speed and efficiency of machine learning. The technology is designed to be 100x faster at initial training thanks to its built-in regularization algorithm which eliminates the hyperparameter optimization step.

Core Features and Capabilities

Perpetual ML offers a range of features including Continual Learning, More Confident Decisions, Better Geography Learning, Model Monitoring, ML Tasks, Portability, Effortless Parallelism, and No specialized hardware requirement.

User Experience

Perpetual ML provides an intuitive user experience, allowing users to easily monitor models and detect distribution shifts with confidence. It is suitable for various tasks including tabular classification, regression, time series, learning to rank tasks and text classification by using embeddings.

Applications and Use Cases

Perpetual ML can be applied across different scenarios or sectors. It is not locked into a single ecosystem and is portable to Python, C, C++, R, Java, Scala, Swift, Julia thanks to all built-in features and its Rust backend.

Impact and Future Outlook

Perpetual ML is set to revolutionize the machine learning industry by providing a faster and more efficient way of training models. It is expected to continue evolving, with future developments focused on enhancing its capabilities and user experience.