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Data Science Decoded

Mike E
We discuss seminal mathematical papers (sometimes really old 😎 ) that have shaped and established the fields of machine learning and data science as we know them today. The goal of the podcast is to introduce you to the evolution of these fields from a mathematical and slightly philosophical perspective.

We will discuss the contribution of these papers, not just from pure a math aspect but also how they influenced the discourse in the field, which areas were opened up as a result, and so on.

Our podcast episodes are also available on our youtube:
https://youtu.be/wThcXx_vXjQ?si=vnMfs

Top mentioned books

Here are the most frequently recommended books on the Data Science Decoded podcast:
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#1 Mentioned in 1 episodes

Simulation

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Sheldon M. Ross
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#2 Mentioned in 1 episodes

A Mathematical Theory of Communication

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Claude Shannon
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#3 Mentioned in 1 episodes

Understanding Probability with Python

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Nir
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