Data Science #34 - The deep learning original paper review, Hinton, Rumelhard & Williams (1985)
On 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 training neural networks...
23 Nov 202546min
Data Science #33 - The Backpropagation method, Paul Werbos (1980)
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 re...
3 Nov 202557min
Data Science #31 - Correlation and causation (1921), Wright Sewall
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 provi...
26 Juli 202548min
Data Science #30 - The Bootstrap Method (1977)
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...
30 Maj 202541min
Data Science #29 - The Chi-square automatic interaction detection(CHAID) algorithm (1979)
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 introdu...
23 Maj 202541min
Data Science #28 - The Bloom filter algorithm
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 o...
23 Maj 202539min
Data Science #27 - The History of Least Squares (1877)
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...
2 Apr 202532min
