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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Data Science Decoded
Visar 1–10 av 33 avsnitt
23 november 2025
Data Science #34 - The deep learning original paper review, Hinton, Rumelhard & Williams (1985)
47 min
3 november 2025
Data Science #33 - The Backpropagation method, Paul Werbos (1980)
58 min
19 september 2025
Data Science #32 - A Markovian Decision Process, Richard Bellman (1957)
46 min
26 juli 2025
Data Science #31 - Correlation and causation (1921), Wright Sewall
48 min
30 maj 2025
Data Science #30 - The Bootstrap Method (1977)
41 min
23 maj 2025
Data Science #29 - The Chi-square automatic interaction detection(CHAID) algorithm (1979)
41 min
23 maj 2025
Data Science #28 - The Bloom filter algorithm
39 min
2 april 2025
Data Science #27 - The History of Least Squares (1877)
32 min
23 mars 2025
Data Science #26 - The First Gradient decent algorithm by Cauchy (1847)
33 min
4 februari 2025
Data Science #24 - The Expectation Maximization (EM) algorithm Paper review (1977)
33 min
