Unlocking the Secrets of Machine Learning: How to Interpret Black Box Models 🔍

Interpretable machine learning (part 1): Peeking into the black box

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Interpreting machine learning models is one of the new hot areas in data science. As calls for greater transparency in algorithms become stronger, researchers have come up with ways to peek into the black box of machine learning.

This video has been produced by the Tesseract Academy (http://tesseract.academy), a company that educates decision makers in deep technical topics such as data science, analytics, machine learning, AI and blockchain.

Read more about the subject at The Data Scientist: http://thedatascientist.com/interpretable-machine-learning/

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About Dr Kampakis

Dr Stylianos (Stelios) Kampakis is a data scientist and tokenomics expert with more than 10 years of experience.

He has worked with companies of all sizes: from startups to organisations like the US Navy, Vodafone and British Land. His work expands multiple sectors including fintech, sports analytics, health-tech, general AI, medical statistics, predictive maintenance and others.

He has worked with many different types of technologies, from statistical models, to deep learning, to large language models. He has 2 patents pending to his name, and has published 3 books on data science, AI and data strategy.

He has helped many people follow a career in data science and technology.

His seminal work in token economics has led to many successful token economic designs using tools such as agent based modelling and game theory.

He is a member of the Royal Statistical Society, honorary research fellow at the UCL Centre for Blockchain Technologies, a data science advisor for London Business School and CEO of The Tesseract Academy.

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#AI #ai #data #datascience #dataanalytics #datanalytics #analytics #artificial_intelligence #bigdata #tokenomics #web3.0 #web3 #blockchain #crypto