ABSTRACT
Coinbase's mission is "to create an open financial system for the world". This presentation serves as an overview of our efforts in building the state-of-the-art machine learning technology for the fast-evolving crypto economy, which follows a prototype, productization, and experimentation development cycle. On the machine learning side, it covers topics around proper train/validation setup, maintaining a fast iteration cycle using a custom-built AutoML framework (called "EasyML"), a deep learning Transformers-based sequence based model and how to incorporate timing into it, how to combine gradient boosting trees with deep learning using linear blending, as well as model interpretability, evaluation, and experimentation. On the machine learning platform side, we will dive into the internals of Nostradamus, our in-house-built framework that manages model life-cycle, and Feature Store, our self-serve feature management, computation and serving framework.
Index Terms
- Build the State-of-the-Art Machine Learning Technology for the Crypto Economy
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