Probability and Statistics for Machine Learning

Files:

• 81-10.6 Categorical 'Dummy' Features.mp4 (633.8 MB)
• 42-5.3 The Central Limit Theorem.mp4 (592.9 MB)
• 65-8.3 Paired t-tests.mp4 (584.0 MB)
• 88-11.4 Bayes' Theorem.mp4 (569.0 MB)
• 60-7.5 p-values.mp4 (562.7 MB)
• 78-10.3 Fitting a Line to Points on a Cartesian Plane.mp4 (538.3 MB)
• 29-3.9 Covariance, a Measure of Relatedness.mp4 (525.9 MB)
• 09-1.7 The Law of Large Numbers and the Gambler's Fallacy.mp4 (517.8 MB)
• 63-8.1 Single-Sample t-tests and Degrees of Freedom.mp4 (477.6 MB)
• 64-8.2 Independent t-tests.mp4 (475.3 MB)
• 26-3.6 Variance, a Measure of Dispersion.mp4 (467.8 MB)
• 82-10.7 Logistic Regression to Predict Categories.mp4 (458.8 MB)
• 57-7.2 Review of Essential Probability Theory.mp4 (450.6 MB)
• 80-10.5 Ordinary Least Squares.mp4 (449.3 MB)
• 58-7.3 z-scores and Outliers.mp4 (410.7 MB)
• 68-8.6 Confidence Intervals.mp4 (382.2 MB)
• 41-5.2 Gaussian - Normal and Standard Normal.mp4 (376.0 MB)
• 30-3.10. Correlation.mp4 (375.6 MB)
• 25-3.5 Box-and-Whisker Plots.mp4 (367.4 MB)
• 56-7.1 Applications of Statistics to Machine Learning.mp4 (357.9 MB)
• 11-1.9 Bayesian versus Frequentist Statistics.mp4 (355.6 MB)
• 21-3.1 The Mean, a Measure of Central Tendency.mp4 (351.5 MB)
• 08-1.6 Exercises.mp4 (350.6 MB)
• 35-4.4 Exercises.mp4 (347.9 MB)
• 45-5.6 Binomial and Multinomial.mp4 (341.3 MB)
• 24-3.4 Quantiles - Percentiles, Quartiles, and Deciles.mp4 (334.0 MB)
• 53-6.3 Shannon and Differential Entropy.mp4 (314.1 MB)
• 66-8.4 Applications to Machine Learning.mp4 (302.5 MB)
• 73-9.3 Correlation versus Causation.mp4 (270.5 MB)
• 06-1.4 Multiple Observations.mp4 (269.2 MB)
• 23-3.3 Modes.mp4 (266.2 MB)
• 19-2.6 Exercises on Expected Value.mp4 (264.1 MB)
• 71-9.1 The Pearson Correlation Coefficient.mp4 (260.9 MB)
• 12-1.10 Applications of Probability to Machine Learning.mp4 (258.3 MB)
• 54-6.4 Kullback-Leibler Divergence and Cross-Entropy.mp4 (246.7 MB)
• 07-1.5 Factorials and Combinatorics.mp4 (245.6 MB)
• 67-8.5 Exercises.mp4 (245.0 MB)
• 01-Probability and Statistics for Machine Learning - Introduction.mp4 (239.7 MB)
• 28-3.8 Standard Error.mp4 (234.9 MB)
• 59-7.4 Exercises on z-scores.mp4 (231.6 MB)
• 61-7.6 Exercises on p-values.mp4 (231.5 MB)
• 05-1.3 Events and Sample Spaces.mp4 (229.1 MB)
• 85-11.1 Machine Learning versus Frequentist Statistics.mp4 (227.1 MB)
• 77-10.2 Linear Regression to Predict Continuous Values.mp4 (220.9 MB)
• 10-1.8 Probability Distributions in Statistics.mp4 (210.7 MB)
• 74-9.4 Correcting for Multiple Comparisons.mp4 (209.7 MB)
• 04-1.2 What Probability Theory Is.mp4 (204.0 MB)
• 44-5.5 Exponential and Laplace.mp4 (191.2 MB)
• 79-10.4 Linear Least Squares Exercise.mp4 (177.2 MB)
• 52-6.2 Self-Information, Nats, and Bits.mp4 (171.8 MB)
• 87-11.3 Prior Probabilities.mp4 (166.7 MB)
• 69-8.7 ANOVA - Analysis of Variance.mp4 (165.0 MB)
• 83-10.8 Open-Ended Exercises.mp4 (163.9 MB)
• 34-4.3 Conditional Probability.mp4 (163.0 MB)
• 46-5.7 Poisson.mp4 (158.5 MB)
• 27-3.7 Standard Deviation.mp4 (155.5 MB)
• 18-2.5 Expected Value.mp4 (150.9 MB)
• 47-5.8 Mixture Distributions.mp4 (150.8 MB)
• 17-2.4 Exercises on Probability Functions.mp4 (147.6 MB)
• 33-4.2 Marginal Probability.mp4 (146.8 MB)
• 72-9.2 R-squared Coefficient of Determination.mp4 (144.6 MB)
• 38-4.7 Conditional Independence.mp4 (138.7 MB)
• 15-2.2 Probability Mass Functions.mp4 (132.3 MB)
• 40-5.1 Uniform.mp4 (130.1 MB)
• 48-5.9 Preprocessing Data for Model Input.mp4 (124.9 MB)
• 43-5.4 Log-Normal.mp4 (113.3 MB)
• 14-2.1 Discrete and Continuous Variables.mp4 (112.3 MB)
• 36-4.5 Chain Rule of Probabilities.mp4 (112.3 MB)
• 22-3.2 Medians.mp4 (111.3 MB)
• 76-10.1 Independent versus Dependent Variables.mp4 (105.6 MB)
• 16-2.3 Probability Density Functions.mp4 (104.9 MB)
• 37-4.6 Independent Random Variables.mp4 (100.7 MB)
• 03-1.1 Orientation to the Machine Learning Foundations Series.mp4 (97.8 MB)
• 32-4.1 Joint Probability Distribution.mp4 (89.2 MB)
• 89-11.5 Resources for Further Study of Probability and Statistics.mp4 (75.2 MB)
• 90-Probability and Statistics for Machine Learning - Summary.mp4 (73.7 MB)
• 86-11.2 When to Use Bayesian Statistics.mp4 (70.6 MB)
• 75-Topics.mp4 (50.4 MB)
• 49-5.10 Exercises.mp4 (48.5 MB)
• 39-Topics.mp4 (46.7 MB)
• 02-Topics.mp4 (40.8 MB)
• 84-Topics.mp4 (39.6 MB)
• 51-6.1 What Information Theory Is.mp4 (39.5 MB)
• 62-Topics.mp4 (38.9 MB)
• 13-Topics.mp4 (38.8 MB)
• 55-Topics.mp4 (38.7 MB)
• 70-Topics.mp4 (33.4 MB)
• 50-Topics.mp4 (30.4 MB)
• 20-Topics.mp4 (23.3 MB)
• 31-Topics.mp4 (21.9 MB)

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