3:28Big black hole eats little black hole (with tidal distortion)
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52:30Markov Chain Lecture 15: Birth and death processes and their stationary distribution
A 52-minute video from molypath: “Markov Chain Lecture 15: Birth and death processes and their stationary distribution”.
58:40Markov Chains Lecture 10: branching processes, Galton-Watson processes
A 59-minute video from molypath: “Markov Chains Lecture 10: branching processes, Galton-Watson processes”.
45:49Markov Chains Lecture 11: extinction in Galton-Watson processes
A 46-minute video from molypath: “Markov Chains Lecture 11: extinction in Galton-Watson processes”.
41:48Markov Chains Lecture 12: branching process example (3-child scheme) and Markov processes
A 42-minute video from molypath: “Markov Chains Lecture 12: branching process example (3-child scheme) and Markov processes”.
51:15Markov Chains Lecture 13: Markov processes, sojourn time, and the infinitesimal generator matrix
A 51-minute video from molypath: “Markov Chains Lecture 13: Markov processes, sojourn time, and the infinitesimal generator matrix”.
1:09:26Markov Chains Lecture 14: Poisson process and the muon lifetime dilemma
A 69-minute video from molypath: “Markov Chains Lecture 14: Poisson process and the muon lifetime dilemma”.
45:26Markov Chains Lecture 16: Queues, or Queuing systems, and their stationary distributions
A 45-minute video from molypath: “Markov Chains Lecture 16: Queues, or Queuing systems, and their stationary distributions”.
47:31Markov Chains Lecture 17: more queuing system details including Erlang's loss formula
A 48-minute video from molypath: “Markov Chains Lecture 17: more queuing system details including Erlang's loss formula”.
44:18Markov Chains Lecture 18: hidden Markov models and two queues.
A 44-minute video from molypath: “Markov Chains Lecture 18: hidden Markov models and two queues.”.
51:48Markov Chains Lecture 19: hidden Markov model details
A 52-minute video from molypath: “Markov Chains Lecture 19: hidden Markov model details”.
42:28Markov Chains Lecture 20: hidden Markov model forward algorithm
A 42-minute video from molypath: “Markov Chains Lecture 20: hidden Markov model forward algorithm”.
52:19Markov Chains Lecture 2: review of probability and random variables
A 52-minute video from molypath: “Markov Chains Lecture 2: review of probability and random variables”.
58:02Markov Chains Lecture 3: finish review with generating functions, start Markov chains
A 58-minute video from molypath: “Markov Chains Lecture 3: finish review with generating functions, start Markov chains”.
1:02:25Markov Chains Lecture 4: directed graphs, transition matrices, and Chapman-Kolmogorov equations.
A 62-minute video from molypath: “Markov Chains Lecture 4: directed graphs, transition matrices, and Chapman-Kolmogorov equations.”.
1:04:44Markov Chains Lecture 5: State occupation distribution vectors & classification of states
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47:49Markov Chains Lecture 6: communicating classes and stationary distribution vectors
A 48-minute video from molypath: “Markov Chains Lecture 6: communicating classes and stationary distribution vectors”.
1:01:06Markov Chains Lecture 7: random walks and gambler's ruin
A 61-minute video from molypath: “Markov Chains Lecture 7: random walks and gambler's ruin”.
54:41Markov Chains Lecture 8: absorption times for gambler's ruin
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49:35Markov Chains Lecture 9: unrestricted random walks
A 50-minute video from molypath: “Markov Chains Lecture 9: unrestricted random walks”.
53:10Multivariate Analysis 10: Units and Standardization in principal component analysis
A 53-minute video from molypath: “Multivariate Analysis 10: Units and Standardization in principal component analysis”.
39:51Multivariate Analysis 11: tuning loadings, and 3 examples: economics, genetics, and computer vision
A 40-minute video from molypath: “Multivariate Analysis 11: tuning loadings, and 3 examples: economics, genetics, and computer vision”.
38:01Multivariate Analysis 12: Interpreting Principal Components, and some general weaknesses of PCA
A 38-minute video from molypath: “Multivariate Analysis 12: Interpreting Principal Components, and some general weaknesses of PCA”.
53:09Multivariate Analysis 13: Distances and Similarities
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54:18Multivariate Analysis 14: MultiDimensional Scaling
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37:38Multivariate Analysis 15: MultiDimensional Scaling Code Example
A 38-minute video from molypath: “Multivariate Analysis 15: MultiDimensional Scaling Code Example”.
34:00Multivariate Analysis 18: Cluster Analysis Overview
A 34-minute video from molypath: “Multivariate Analysis 18: Cluster Analysis Overview”.
41:54Multivariate Analysis 1: mathematical preliminaries, matrices and matrix algebra
A 42-minute video from molypath: “Multivariate Analysis 1: mathematical preliminaries, matrices and matrix algebra”.
49:36Multivariate Analysis 2: vectors, eigenvectors, and eigenvalues
A 50-minute video from molypath: “Multivariate Analysis 2: vectors, eigenvectors, and eigenvalues”.
50:37Multivariate Analysis 3: Covariance matrix, correlation matrix, data cloud
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31:24Multivariate Analysis 4: Motivating Exploratory Data Analysis
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1:03:13Multivariate Analysis 5: Tools of Exploratory Data Analysis
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56:49Multivariate Analysis 6: Motivating Principal Component Analysis (PCA)
A 57-minute video from molypath: “Multivariate Analysis 6: Motivating Principal Component Analysis (PCA)”.
1:03:42Multivariate Analysis 7: Mathematics of Principal Component Analysis (PCA)
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54:05Multivariate Analysis 8: Principle Component Analysis Examples
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47:56Multivariate Analysis 9: PCA, Singular Value Decomposition (SVD), and the pseudoinverse of a matrix
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