Description
Perpetual ML is an AI tool employing Perpetual Learning technology to significantly speed up model training. This acceleration is mainly due to the elimination of the hyperparameter optimization phase, which substantially enhances speed.
It provides functionalities such as quick initial training using an integrated regularization algorithm, the advantage of continual learning allowing incremental model training without starting over for each new dataset, and improved decision confidence via integrated Conformal Prediction algorithms.
Furthermore, it offers methods to enhance the learning of geographical decision boundaries and includes a feature for model monitoring and distribution shift detection.
The platform supports various machine learning tasks like tabular classification, regression, time-series analysis, learning to rank, and text classification, among others.
Thanks to its Rust backend, it's portable across programming languages like Python, C, C++, R, Java, Scala, Swift, and Julia. Designed for computational efficiency, Perpetual ML doesn't need specialized hardware to operate.
Pricing Plans
Releases
Reviews
Pros & Cons
Pros
Speeds up model training processes
Eliminates hyperparameter optimization requirements
Provides initial rapid training capabilities
Cons
Doesn't need hardware specialization
Lacks hyperparameter optimization
Requires constant retraining
