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

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

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

Data Science #28 - The Bloom filter algorithm

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

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

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

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

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

Data Science #21 - Steps Toward Artificial Intelligence

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

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

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

Data Science #17 - The Monte Carlo Algorithm (1949)

Data Science #16 - The First Stochastic Descent Algorithm (1952)

Data Science #15 - The First Decision Tree Algorithm (1963)

Data Science #14 - The original k-means algorithm paper review (1957)

Data Science #13 - Kolmogorov complexity paper review (1965) - Part 2

Data Science #12 - Kolmogorov complexity paper review (1965) - Part 1

Data Science #11 - The original Perceptron paper by Frank Rosenblatt (1958)