We are an Machine Learning Studio (Dream Faster), developing the Financial Machine Learning platform (Myalo).
Through Myalo's platform we are bringing much-needed transparency, speed and rigour to the process of building interpretable, reproducable time-series pipelines.
If you are a quant researcher, a fund manager or generally interested in modeling financial data get in touch with us at contact@myalo.finance
More details on our website: https://www.myalo.finance/
🪁 A fast Adaptive Machine Learning library for Time-Series, that lets you build, deploy and update composite models easily. An order of magnitude speed-up, combined with flexibility and rigour. This is an internal project - documentation is not updated anymore and substantially differ from the current API.
🧱 Wrappers for 3rd party models to be used with fold (https://github.com/dream-faster/fold)
⚙️ Speedy implementations of TS Models, built specifically for Fold (https://github.com/dream-faster/fold)
Simple python script to add/replace license headers in a directory tree of source files
🐾 A lightweight & extensible library to create complex multi-model and multi-modal pipelines, including ``Ensembles`` and ``Meta-Models``
🎙 Hate-speech detection Demo API built with Modular Pipelines: https://github.com/applied-exploration/modular-pipelines
⛓️ laplace is an end-to-end ML framework to train and predict on neurally-enhanced graphs for recommendation. The pipeline is designed for self-supervised edge prediction on heterogenous graphs.
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