10 Patterns of Centralized Crypto Exchanges Explained Using Machine Learning and Data Visualizations

Written by jrodthoughts | Published 2019/10/08
Tech Story Tags: ethereum | cryptocurrency | data-science | machine-learning | intotheblock | latest-tech-stories | centralized-crypto-exchanges | hackernoon-top-story

TLDR At IntoTheBlock, we have been working on a series of machine learning models that help us better understand the internal behavior of centralized crypto exchanges. Anonymity, non-standard blockchain reconciliation procedures and regular wash trading behaviors are some of the factors that challenge most analyses of centralized exchanges. Ensemble Learning can be used to combine multiple models into a single knowledge structure that can understand internal patterns of centralized crypto exchanges, such as deposit or withdrawal. Data visualizations have proven to be a unique asset to understand the behavior of the exchanges.via the TL;DR App

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Written by jrodthoughts | Chief Scientist, Managing Partner at Invector Labs. CTO at IntoTheBlock. Angel Investor, Writer, Boa
Published by HackerNoon on 2019/10/08