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0 |
222.83KB |
01-Probability and Statistics for Machine Learning - Introduction.mp4 |
239.66MB |
02-Topics.mp4 |
40.79MB |
03-1.1 Orientation to the Machine Learning Foundations Series.mp4 |
97.76MB |
04-1.2 What Probability Theory Is.mp4 |
204.01MB |
05-1.3 Events and Sample Spaces.mp4 |
229.10MB |
06-1.4 Multiple Observations.mp4 |
269.17MB |
07-1.5 Factorials and Combinatorics.mp4 |
245.56MB |
08-1.6 Exercises.mp4 |
350.65MB |
09-1.7 The Law of Large Numbers and the Gambler's Fallacy.mp4 |
517.83MB |
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1.11MB |
10 |
201.23KB |
10-1.8 Probability Distributions in Statistics.mp4 |
210.66MB |
11 |
1.17MB |
11-1.9 Bayesian versus Frequentist Statistics.mp4 |
355.60MB |
12 |
1.37MB |
12-1.10 Applications of Probability to Machine Learning.mp4 |
258.26MB |
13 |
740.23KB |
13-Topics.mp4 |
38.76MB |
14 |
1.26MB |
14-2.1 Discrete and Continuous Variables.mp4 |
112.33MB |
15 |
1.78MB |
15-2.2 Probability Mass Functions.mp4 |
132.32MB |
16 |
21.47KB |
16-2.3 Probability Density Functions.mp4 |
104.91MB |
17 |
398.74KB |
17-2.4 Exercises on Probability Functions.mp4 |
147.59MB |
18 |
579.15KB |
18-2.5 Expected Value.mp4 |
150.86MB |
19 |
137.14KB |
19-2.6 Exercises on Expected Value.mp4 |
264.14MB |
2 |
14.18KB |
20 |
408.35KB |
20-Topics.mp4 |
23.27MB |
21 |
544.52KB |
21-3.1 The Mean, a Measure of Central Tendency.mp4 |
351.47MB |
22 |
1.35MB |
22-3.2 Medians.mp4 |
111.29MB |
23 |
90.50KB |
23-3.3 Modes.mp4 |
266.20MB |
24 |
726.58KB |
24-3.4 Quantiles - Percentiles, Quartiles, and Deciles.mp4 |
334.05MB |
25 |
1.95MB |
25-3.5 Box-and-Whisker Plots.mp4 |
367.43MB |
26 |
1.92MB |
26-3.6 Variance, a Measure of Dispersion.mp4 |
467.80MB |
27 |
1.47MB |
27-3.7 Standard Deviation.mp4 |
155.49MB |
28 |
1.53MB |
28-3.8 Standard Error.mp4 |
234.92MB |
29 |
850.26KB |
29-3.9 Covariance, a Measure of Relatedness.mp4 |
525.85MB |
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1.03MB |
30 |
1.80MB |
30-3.10. Correlation.mp4 |
375.61MB |
31 |
1.86MB |
31-Topics.mp4 |
21.87MB |
32 |
1.10MB |
32-4.1 Joint Probability Distribution.mp4 |
89.18MB |
33 |
1.74MB |
33-4.2 Marginal Probability.mp4 |
146.85MB |
34 |
1.28MB |
34-4.3 Conditional Probability.mp4 |
163.03MB |
35 |
453.64KB |
35-4.4 Exercises.mp4 |
347.91MB |
36 |
1.04MB |
36-4.5 Chain Rule of Probabilities.mp4 |
112.33MB |
37 |
351.17KB |
37-4.6 Independent Random Variables.mp4 |
100.74MB |
38 |
1.08MB |
38-4.7 Conditional Independence.mp4 |
138.71MB |
39 |
389.26KB |
39-Topics.mp4 |
46.68MB |
4 |
1.28MB |
40 |
485.52KB |
40-5.1 Uniform.mp4 |
130.14MB |
41 |
921.97KB |
41-5.2 Gaussian - Normal and Standard Normal.mp4 |
375.98MB |
42 |
882.81KB |
42-5.3 The Central Limit Theorem.mp4 |
592.89MB |
43 |
1.12MB |
43-5.4 Log-Normal.mp4 |
113.29MB |
44 |
1.34MB |
44-5.5 Exponential and Laplace.mp4 |
191.19MB |
45 |
332.25KB |
45-5.6 Binomial and Multinomial.mp4 |
341.29MB |
46 |
1.99MB |
46-5.7 Poisson.mp4 |
158.49MB |
47 |
826.12KB |
47-5.8 Mixture Distributions.mp4 |
150.85MB |
48 |
857.77KB |
48-5.9 Preprocessing Data for Model Input.mp4 |
124.93MB |
49 |
183.82KB |
49-5.10 Exercises.mp4 |
48.54MB |
5 |
1.72MB |
50 |
1.32MB |
50-Topics.mp4 |
30.45MB |
51 |
1.01MB |
51-6.1 What Information Theory Is.mp4 |
39.54MB |
52 |
97.55KB |
52-6.2 Self-Information, Nats, and Bits.mp4 |
171.82MB |
53 |
991.68KB |
53-6.3 Shannon and Differential Entropy.mp4 |
314.08MB |
54 |
1.51MB |
54-6.4 Kullback-Leibler Divergence and Cross-Entropy.mp4 |
246.72MB |
55 |
524.77KB |
55-Topics.mp4 |
38.74MB |
56 |
1.14MB |
56-7.1 Applications of Statistics to Machine Learning.mp4 |
357.87MB |
57 |
1.15MB |
57-7.2 Review of Essential Probability Theory.mp4 |
450.63MB |
58 |
424.58KB |
58-7.3 z-scores and Outliers.mp4 |
410.74MB |
59 |
1.15MB |
59-7.4 Exercises on z-scores.mp4 |
231.62MB |
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149.29KB |
60 |
1.40MB |
60-7.5 p-values.mp4 |
562.72MB |
61 |
1.29MB |
61-7.6 Exercises on p-values.mp4 |
231.53MB |
62 |
1.68MB |
62-Topics.mp4 |
38.89MB |
63 |
1.86MB |
63-8.1 Single-Sample t-tests and Degrees of Freedom.mp4 |
477.56MB |
64 |
1.07MB |
64-8.2 Independent t-tests.mp4 |
475.31MB |
65 |
723.31KB |
65-8.3 Paired t-tests.mp4 |
583.99MB |
66 |
1.67MB |
66-8.4 Applications to Machine Learning.mp4 |
302.53MB |
67 |
1.67MB |
67-8.5 Exercises.mp4 |
244.96MB |
68 |
731.25KB |
68-8.6 Confidence Intervals.mp4 |
382.22MB |
69 |
454.35KB |
69-8.7 ANOVA - Analysis of Variance.mp4 |
164.99MB |
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172.04KB |
70 |
1.09MB |
70-Topics.mp4 |
33.38MB |
71 |
1.26MB |
71-9.1 The Pearson Correlation Coefficient.mp4 |
260.90MB |
72 |
249.87KB |
72-9.2 R-squared Coefficient of Determination.mp4 |
144.60MB |
73 |
839.76KB |
73-9.3 Correlation versus Causation.mp4 |
270.47MB |
74 |
806.39KB |
74-9.4 Correcting for Multiple Comparisons.mp4 |
209.68MB |
75 |
338.04KB |
75-Topics.mp4 |
50.39MB |
76 |
1.39MB |
76-10.1 Independent versus Dependent Variables.mp4 |
105.56MB |
77 |
1.61MB |
77-10.2 Linear Regression to Predict Continuous Values.mp4 |
220.88MB |
78 |
1.46MB |
78-10.3 Fitting a Line to Points on a Cartesian Plane.mp4 |
538.28MB |
79 |
1.32MB |
79-10.4 Linear Least Squares Exercise.mp4 |
177.16MB |
8 |
446.04KB |
80 |
1.21MB |
80-10.5 Ordinary Least Squares.mp4 |
449.28MB |
81 |
447.05KB |
81-10.6 Categorical 'Dummy' Features.mp4 |
633.78MB |
82 |
473.79KB |
82-10.7 Logistic Regression to Predict Categories.mp4 |
458.83MB |
83 |
1.11MB |
83-10.8 Open-Ended Exercises.mp4 |
163.90MB |
84 |
1.24MB |
84-Topics.mp4 |
39.56MB |
85 |
1.26MB |
85-11.1 Machine Learning versus Frequentist Statistics.mp4 |
227.14MB |
86 |
634.24KB |
86-11.2 When to Use Bayesian Statistics.mp4 |
70.61MB |
87 |
1.55MB |
87-11.3 Prior Probabilities.mp4 |
166.68MB |
88 |
747.80KB |
88-11.4 Bayes' Theorem.mp4 |
568.97MB |
89-11.5 Resources for Further Study of Probability and Statistics.mp4 |
75.21MB |
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709.99KB |
90-Probability and Statistics for Machine Learning - Summary.mp4 |
73.67MB |
TutsNode.com.txt |
61B |