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Data Science #33 - The Backpropagation method, Paul Werbos (1980)

3 नवमबर 2025

On the 33rd episdoe we review Paul Werbos’s “Applications of Advances in Nonlinear Sensitivity Analysis” which presents efficient methods for computing derivatives in nonlinear systems, drastically reducing computational costs for large-scale models. Werbos, Paul J. "Applications of advances…

00:57:45

Data Science #32 - A Markovian Decision Process, Richard Bellman (1957)

19 सितमबर 2025

We reviewed Richard Bellman’s “A Markovian Decision Process” (1957), which introduced a mathematical framework for sequential decision-making under uncertainty. By connecting recurrence relations to Markov processes, Bellman showed how current choices shape future outcomes and formalized the prin…

00:46:05

Data Science #31 - Correlation and causation (1921), Wright Sewall

26 जुलाई 2025

On 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 simple diagrams and proving that any sample correlation can be written as the sum of products of “path coefficients.” By t…

00:48:11

Data Science #30 - The Bootstrap Method (1977)

30 मई 2025

In 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 sampling distribution by repeatedly drawing with replacement from the observed data, allowing estimation of standard errors…

00:41:05

Data Science #29 - The Chi-square automatic interaction detection(CHAID) algorithm (1979)

23 मई 2025

In 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 partitioning method introduced by G. V. Kass for exploring large categorical data sets by iteratively splitting records into m…

00:41:03

Data Science #28 - The Bloom filter algorithm

23 मई 2025

In 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 small, controllable rate of false positives.Unlike traditional methods that store full data, Bloom filters use a compact bit …

00:39:15

Data Science #27 - The History of Least Squares (1877)

2 अप्रैल 2025

Mansfield 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 first formal probabilistic proof, and Gauss (1809) for linking it to the normal distribution. He evaluates multiple proofs,…

00:32:09

Data Science #26 - The First Gradient decent algorithm by Cauchy (1847)

23 मार्च 2025

In 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. Instead of elimination, he proposed progressively reducing the function’s value through small updates, forming an early ver…

00:33:14

Data Science #24 - The Expectation Maximization (EM) algorithm Paper review (1977)

4 फ़रवरी 2025

At 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 the royal statistical society: series B (methodological) 39.1 (1977): 1-22.The Expectation-Maximization (EM) algorithm i…

00:32:47