Data Science Decoded

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

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Avsnitt(33)

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

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

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, ...

23 Mars 202533min

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

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

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...

4 Feb 202532min

Data Science #23- The Markov Chain Monte Carl MCMC Paper review (1953)

Data Science #23- The Markov Chain Monte Carl MCMC Paper review (1953)

In 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 (1953): 1087-1092 which...

14 Jan 202537min

Data Science #22 - The theory of dynamic programming, Paper review 1954

Data Science #22 - The theory of dynamic programming, Paper review 1954

We 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. First, his Principle ...

7 Jan 202547min

Data Science #21 - Steps Toward Artificial Intelligence

Data Science #21 - Steps Toward Artificial Intelligence

In 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 that outlines the challen...

25 Dec 202459min

Data Science #20 - the Rao-Cramer bound (1945)

Data Science #20 - the Rao-Cramer bound (1945)

In 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 the estimation of statis...

9 Dec 202459min

Data Science #19 - The Kullback–Leibler divergence paper (1951)

Data Science #19 - The Kullback–Leibler divergence paper (1951)

In 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 probability distributions, quan...

2 Dec 202452min

Data Science #18 - The k-nearest neighbors algorithm (1951)

Data Science #18 - The k-nearest neighbors algorithm (1951)

In the 18th episode we go over the original k-nearest neighbors algorithm; Fix, Evelyn; Hodges, Joseph L. (1951). Discriminatory Analysis. Nonparametric Discrimination: Consistency Properties USAF S...

25 Nov 202444min

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