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Mike E
Data Science Decoded
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
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Recent Episodes
In this episode with go over the Kullback-Leibler (KL) divergence paper, "On Information and Sufficiency" (1951).
It introduced a measure of the difference between two probability distributions, quantifying the cost of assuming one distribution when another is true.
This concept, rooted in...
Published 12/02/24
In the 18th episode we go over the original k-nearest neighbors algorithm;
Fix, Evelyn; Hodges, Joseph L. (1951). Discriminatory Analysis. Nonparametric Discrimination: Consistency Properties USAF School of Aviation Medicine, Randolph Field, Texas
They introduces a nonparametric method for...
Published 11/25/24
Published 11/25/24
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