Data Science Decoded
by Mike E
Latest episode
Data Science #34 - The deep learning original paper review, Hinton…
Data Science #34 - The deep learning original paper review, Hinton…
About this podcast
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
Episodes
The newest 20 of 33 episodes
- Data Science #34 - The deep learning original paper review, Hinton, Rumelhard & Williams (1985) · 47 min · Season 2 Episode 34On the 34th episode, we review the 1986 paper, "Learning representations by back-propagating errors" , which was pivotal because it provided a clear, generalized framework for…
- Data Science #33 - The Backpropagation method, Paul Werbos (1980) · 58 min · Season 2 Episode 33On the 33rd episdoe we review Paul Werbos’s “Applications of Advances in Nonlinear Sensitivity Analysis” which presents efficient methods for computing derivatives in nonlinear…
- Data Science #32 - A Markovian Decision Process, Richard Bellman (1957) · 46 min · Season 2 Episode 32We reviewed Richard Bellman’s “A Markovian Decision Process” (1957), which introduced a mathematical framework for sequential decision-making under uncertainty. By connecting…
- Data Science #31 - Correlation and causation (1921), Wright Sewall · 48 min · Season 2 Episode 4On the 31st episode of the podcast, we add Liron to the team, we review a gem from 1921, where Sewall Wright introduced path analysis, mapping hypothesized causal arrows into…
- Data Science #30 - The Bootstrap Method (1977) · 41 minIn the 30th episode we review the the bootstrap, method which was introduced by Bradley Efron in 1979, is a non-parametric resampling technique that approximates a statistic’s…
- Data Science #29 - The Chi-square automatic interaction detection(CHAID) algorithm (1979) · 41 min · Season 2 Episode 9In the 29th episode, we go over the 1979 paper by Gordon Vivian Kass that introduced the CHAID algorithm.CHAID (Chi-squared Automatic Interaction Detection) is a tree-based…
- Data Science #28 - The Bloom filter algorithm · 39 min · Season 2 Episode 8In the 28th episode, we go over Burton Bloom's Bloom filter from 1970, a groundbreaking data structure that enables fast, space-efficient set membership checks by allowing a…
- Data Science #27 - The History of Least Squares (1877) · 32 min · Season 2 Episode 7Mansfield Merriman's 1877 paper traces the historical development of the Method of Least Squares, crediting Legendre (1805) for introducing the method, Adrain (1808) for the…
- Data Science #26 - The First Gradient decent algorithm by Cauchy (1847) · 33 min · Season 2 Episode 6In this episode, we review Cauchy’s 1847 paper, which introduced an iterative method for solving simultaneous equations by minimizing a function using its partial derivatives…
- Data Science #24 - The Expectation Maximization (EM) algorithm Paper review (1977) · 33 min · Season 2 Episode 4At the 24th episode we go over the paper titled:Dempster, Arthur P., Nan M. Laird, and Donald B. Rubin. "Maximum likelihood from incomplete data via the EM algorithm." Journal of…
- Data Science #23- The Markov Chain Monte Carl MCMC Paper review (1953) · 38 min · Season 2 Episode 12In the 23rd episode we review the The 1953 paper Metropolis, Nicholas, et al. "Equation of state calculations by fast computing machines." The journal of chemical physics 21.6…
- Data Science #22 - The theory of dynamic programming, Paper review 1954 · 48 min · Season 2 Episode 3We review Richard Bellman's "The Theory of Dynamic Programming" paper from 1954 which revolutionized how we approach complex decision-making problems through two key innovations…
- Data Science #21 - Steps Toward Artificial Intelligence · 60 min · Season 2 Episode 1In the 1st episode of the second season we review the legendary Marvin Minsky's "Steps Toward Artificial Intelligence" from 1961. Itis a foundational work in the field of AI…
- Data Science #20 - the Rao-Cramer bound (1945) · 60 min · Season 1 Episode 20In the 20th episode, we review the seminal paper by Rao which introduced the Cramer Rao bound: Rao, Calyampudi Radakrishna (1945). "Information and the accuracy attainable in…
- Data Science #19 - The Kullback–Leibler divergence paper (1951) · 53 min · Season 1 Episode 19In 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…
- Data Science #18 - The k-nearest neighbors algorithm (1951) · 44 min · Season 1 Episode 20In the 18th episode we go over the original k-nearest neighbors algorithm; Fix, Evelyn; Hodges, Joseph L. (1951). Discriminatory Analysis. Nonparametric Discrimination…
- Data Science #17 - The Monte Carlo Algorithm (1949) · 38 min · Season 1 Episode 17We review the original Monte Carlo paper from 1949 by Metropolis, Nicholas, and Stanislaw Ulam. "The monte carlo method." Journal of the American statistical association 44.247…
- Data Science #16 - The First Stochastic Descent Algorithm (1952) · 42 min · Season 1 Episode 16In 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…
- Data Science #15 - The First Decision Tree Algorithm (1963) · 37 min · Season 1 Episode 15the 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…
- Data Science #14 - The original k-means algorithm paper review (1957) · 47 min · Season 1 Episode 14At the 14th episode we go over the Stuart Lloyd's 1957 paper, "Least Squares Quantization in PCM," (which was published only at 1982) The k-means algorithm can be traced back to…
