Is this your podcast?
Sign up
to track ranks and reviews from Spotify, Apple Podcasts and more
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
Listen now
Recent Episodes
In the 16th episode we go over the seminal the 1952 paper titled:
"A stochastic approximation method." The annals of mathematical statistics (1951): 400-407, by Robbins, Herbert and Sutton Monro.
The paper introduced the stochastic approximation method, a groundbreaking iterative technique for...
Published 11/07/24
the 15th episode we went over the paper "Problems in the Analysis of Survey Data, and a Proposal" by James N. Morgan and John A. Sonquist from 1963.
It highlights seven key issues in analyzing complex survey data, such as high dimensionality, categorical variables, measurement errors, sample...
Published 10/28/24
Published 10/28/24
Do you host a podcast?
Track your ranks and reviews from Spotify, Apple Podcasts and more.
Links
Twitter
Facebook
Instagram
Patreon
Genres
Artwork or description wrong?
Request an update »
Updates may take a few minutes.
Do you host a podcast?
Track your ranks and reviews from Spotify, Apple Podcasts and more.
