
FinMLKit: A financial ML toolkit
The main goal of this python library is to provide a solid foundation for financial machine learning, enabling users to process raw trades data, generate different types of bars, intra-bar features (eg. footprints), bar-level features (indicators), and labels for supervised learning. It tackles three chronic causes of unreliable results in the field: time-based sampling bias, weak labels, and throughput constraints that make rigorous methods hard to apply at scale.
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