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[Tutorialsplanet.NET] Udemy - Master statistics & machine learning - intuition, math, code

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File Name
Size
01 - Introductions/001 [Important] Getting the most out of this course.mp4
38 MB
01 - Introductions/001 [Important] Getting the most out of this course_en.srt
6.1 kB
01 - Introductions/001 [Important] Getting the most out of this course_en.vtt
5.4 kB
01 - Introductions/002 About using MATLAB or Python.mp4
27 MB
01 - Introductions/002 About using MATLAB or Python_en.srt
5.9 kB
01 - Introductions/002 About using MATLAB or Python_en.vtt
5.2 kB
01 - Introductions/003 Statistics guessing game_.mp4
48 MB
01 - Introductions/003 Statistics guessing game__en.srt
13 kB
01 - Introductions/003 Statistics guessing game__en.vtt
12 kB
01 - Introductions/004 Using the Q&A forum.mp4
24 MB
01 - Introductions/004 Using the Q&A forum_en.srt
8.1 kB
01 - Introductions/004 Using the Q&A forum_en.vtt
7.1 kB
01 - Introductions/005 (optional) Entering time-stamped notes in the Udemy video player.mp4
7.1 MB
01 - Introductions/005 (optional) Entering time-stamped notes in the Udemy video player_en.srt
3.1 kB
01 - Introductions/005 (optional) Entering time-stamped notes in the Udemy video player_en.vtt
2.7 kB
01 - Introductions/25299297-stats-intro-GuessTheTest.zip
3.7 kB
01 - Introductions/[Tutorialsplanet.NET].url
128 B
02 - Math prerequisites/001 Should you memorize statistical formulas_.mp4
28 MB
02 - Math prerequisites/001 Should you memorize statistical formulas__en.srt
4.2 kB
02 - Math prerequisites/001 Should you memorize statistical formulas__en.vtt
3.7 kB
02 - Math prerequisites/002 Arithmetic and exponents.mp4
7.6 MB
02 - Math prerequisites/002 Arithmetic and exponents_en.srt
5.6 kB
02 - Math prerequisites/002 Arithmetic and exponents_en.vtt
4.9 kB
02 - Math prerequisites/003 Scientific notation.mp4
13 MB
02 - Math prerequisites/003 Scientific notation_en.srt
8.7 kB
02 - Math prerequisites/003 Scientific notation_en.vtt
7.5 kB
02 - Math prerequisites/004 Summation notation.mp4
7.7 MB
02 - Math prerequisites/004 Summation notation_en.srt
6.0 kB
02 - Math prerequisites/004 Summation notation_en.vtt
5.2 kB
02 - Math prerequisites/005 Absolute value.mp4
6.9 MB
02 - Math prerequisites/005 Absolute value_en.srt
4.2 kB
02 - Math prerequisites/005 Absolute value_en.vtt
3.7 kB
02 - Math prerequisites/006 Natural exponent and logarithm.mp4
12 MB
02 - Math prerequisites/006 Natural exponent and logarithm_en.srt
8.1 kB
02 - Math prerequisites/006 Natural exponent and logarithm_en.vtt
7.0 kB
02 - Math prerequisites/007 The logistic function.mp4
18 MB
02 - Math prerequisites/007 The logistic function_en.srt
13 kB
02 - Math prerequisites/007 The logistic function_en.vtt
11 kB
02 - Math prerequisites/008 Rank and tied-rank.mp4
13 MB
02 - Math prerequisites/008 Rank and tied-rank_en.srt
9.5 kB
02 - Math prerequisites/008 Rank and tied-rank_en.vtt
8.2 kB
03 - IMPORTANT_ Download course materials/001 Download materials for the entire course_.mp4
14 MB
03 - IMPORTANT_ Download course materials/001 Download materials for the entire course__en.srt
5.4 kB
03 - IMPORTANT_ Download course materials/001 Download materials for the entire course__en.vtt
4.8 kB
03 - IMPORTANT_ Download course materials/32684220-statsML.zip
1.4 MB
04 - What are (is_) data_/001 Is _data_ singular or plural_______.mp4
11 MB
04 - What are (is_) data_/001 Is _data_ singular or plural________en.srt
2.3 kB
04 - What are (is_) data_/001 Is _data_ singular or plural________en.vtt
2.0 kB
04 - What are (is_) data_/002 Where do data come from and what do they mean_.mp4
36 MB
04 - What are (is_) data_/002 Where do data come from and what do they mean__en.srt
8.4 kB
04 - What are (is_) data_/002 Where do data come from and what do they mean__en.vtt
7.3 kB
04 - What are (is_) data_/003 Types of data_ categorical, numerical, etc.mp4
59 MB
04 - What are (is_) data_/003 Types of data_ categorical, numerical, etc_en.srt
21 kB
04 - What are (is_) data_/003 Types of data_ categorical, numerical, etc_en.vtt
18 kB
04 - What are (is_) data_/004 Code_ representing types of data on computers.mp4
48 MB
04 - What are (is_) data_/004 Code_ representing types of data on computers_en.srt
13 kB
04 - What are (is_) data_/004 Code_ representing types of data on computers_en.vtt
11 kB
04 - What are (is_) data_/005 Sample vs. population data.mp4
37 MB
04 - What are (is_) data_/005 Sample vs. population data_en.srt
17 kB
04 - What are (is_) data_/005 Sample vs. population data_en.vtt
15 kB
04 - What are (is_) data_/006 Samples, case reports, and anecdotes.mp4
18 MB
04 - What are (is_) data_/006 Samples, case reports, and anecdotes_en.srt
7.7 kB
04 - What are (is_) data_/006 Samples, case reports, and anecdotes_en.vtt
6.7 kB
04 - What are (is_) data_/007 The ethics of making up data.mp4
20 MB
04 - What are (is_) data_/007 The ethics of making up data_en.srt
10 kB
04 - What are (is_) data_/007 The ethics of making up data_en.vtt
8.9 kB
05 - Visualizing data/001 Bar plots.mp4
37 MB
05 - Visualizing data/001 Bar plots_en.srt
17 kB
05 - Visualizing data/001 Bar plots_en.vtt
15 kB
05 - Visualizing data/002 Code_ bar plots.mp4
100 MB
05 - Visualizing data/002 Code_ bar plots_en.srt
25 kB
05 - Visualizing data/002 Code_ bar plots_en.vtt
23 kB
05 - Visualizing data/003 Box-and-whisker plots.mp4
11 MB
05 - Visualizing data/003 Box-and-whisker plots_en.srt
7.8 kB
05 - Visualizing data/003 Box-and-whisker plots_en.vtt
6.8 kB
05 - Visualizing data/004 Code_ box plots.mp4
84 MB
05 - Visualizing data/004 Code_ box plots_en.srt
13 kB
05 - Visualizing data/004 Code_ box plots_en.vtt
11 kB
05 - Visualizing data/005 _Unsupervised learning__ Boxplots of normal and uniform noise.mp4
8.2 MB
05 - Visualizing data/005 _Unsupervised learning__ Boxplots of normal and uniform noise_en.srt
3.7 kB
05 - Visualizing data/005 _Unsupervised learning__ Boxplots of normal and uniform noise_en.vtt
3.3 kB
05 - Visualizing data/006 Histograms.mp4
44 MB
05 - Visualizing data/006 Histograms_en.srt
16 kB
05 - Visualizing data/006 Histograms_en.vtt
14 kB
05 - Visualizing data/007 Code_ histograms.mp4
134 MB
05 - Visualizing data/007 Code_ histograms_en.srt
24 kB
05 - Visualizing data/007 Code_ histograms_en.vtt
21 kB
05 - Visualizing data/008 _Unsupervised learning__ Histogram proportion.mp4
12 MB
05 - Visualizing data/008 _Unsupervised learning__ Histogram proportion_en.srt
3.4 kB
05 - Visualizing data/008 _Unsupervised learning__ Histogram proportion_en.vtt
3.0 kB
05 - Visualizing data/009 Pie charts.mp4
16 MB
05 - Visualizing data/009 Pie charts_en.srt
8.5 kB
05 - Visualizing data/009 Pie charts_en.vtt
7.3 kB
05 - Visualizing data/010 Code_ pie charts.mp4
79 MB
05 - Visualizing data/010 Code_ pie charts_en.srt
19 kB
05 - Visualizing data/010 Code_ pie charts_en.vtt
17 kB
05 - Visualizing data/011 When to use lines instead of bars.mp4
18 MB
05 - Visualizing data/011 When to use lines instead of bars_en.srt
8.6 kB
05 - Visualizing data/011 When to use lines instead of bars_en.vtt
7.5 kB
05 - Visualizing data/012 Linear vs. logarithmic axis scaling.mp4
26 MB
05 - Visualizing data/012 Linear vs. logarithmic axis scaling_en.srt
12 kB
05 - Visualizing data/012 Linear vs. logarithmic axis scaling_en.vtt
11 kB
05 - Visualizing data/013 Code_ line plots.mp4
37 MB
05 - Visualizing data/013 Code_ line plots_en.srt
11 kB
05 - Visualizing data/013 Code_ line plots_en.vtt
9.4 kB
05 - Visualizing data/014 _Unsupervised learning__ log-scaled plots.mp4
3.7 MB
05 - Visualizing data/014 _Unsupervised learning__ log-scaled plots_en.srt
2.5 kB
05 - Visualizing data/014 _Unsupervised learning__ log-scaled plots_en.vtt
2.1 kB
06 - Descriptive statistics/001 Descriptive vs. inferential statistics.mp4
22 MB
06 - Descriptive statistics/001 Descriptive vs. inferential statistics_en.srt
6.4 kB
06 - Descriptive statistics/001 Descriptive vs. inferential statistics_en.vtt
5.6 kB
06 - Descriptive statistics/002 Accuracy, precision, resolution.mp4
25 MB
06 - Descriptive statistics/002 Accuracy, precision, resolution_en.srt
11 kB
06 - Descriptive statistics/002 Accuracy, precision, resolution_en.vtt
9.8 kB
06 - Descriptive statistics/003 Data distributions.mp4
32 MB
06 - Descriptive statistics/003 Data distributions_en.srt
17 kB
06 - Descriptive statistics/003 Data distributions_en.vtt
14 kB
06 - Descriptive statistics/004 Code_ data from different distributions.mp4
303 MB
06 - Descriptive statistics/004 Code_ data from different distributions_en.srt
46 kB
06 - Descriptive statistics/004 Code_ data from different distributions_en.vtt
40 kB
06 - Descriptive statistics/005 _Unsupervised learning__ histograms of distributions.mp4
10 MB
06 - Descriptive statistics/005 _Unsupervised learning__ histograms of distributions_en.srt
3.1 kB
06 - Descriptive statistics/005 _Unsupervised learning__ histograms of distributions_en.vtt
2.6 kB
06 - Descriptive statistics/006 The beauty and simplicity of Normal.mp4
10 MB
06 - Descriptive statistics/006 The beauty and simplicity of Normal_en.srt
7.6 kB
06 - Descriptive statistics/006 The beauty and simplicity of Normal_en.vtt
6.7 kB
06 - Descriptive statistics/007 Measures of central tendency (mean).mp4
39 MB
06 - Descriptive statistics/007 Measures of central tendency (mean)_en.srt
19 kB
06 - Descriptive statistics/007 Measures of central tendency (mean)_en.vtt
16 kB
06 - Descriptive statistics/008 Measures of central tendency (median, mode).mp4
34 MB
06 - Descriptive statistics/008 Measures of central tendency (median, mode)_en.srt
18 kB
06 - Descriptive statistics/008 Measures of central tendency (median, mode)_en.vtt
16 kB
06 - Descriptive statistics/009 Code_ computing central tendency.mp4
67 MB
06 - Descriptive statistics/009 Code_ computing central tendency_en.srt
20 kB
06 - Descriptive statistics/009 Code_ computing central tendency_en.vtt
17 kB
06 - Descriptive statistics/010 _Unsupervised learning__ central tendencies with outliers.mp4
17 MB
06 - Descriptive statistics/010 _Unsupervised learning__ central tendencies with outliers_en.srt
4.3 kB
06 - Descriptive statistics/010 _Unsupervised learning__ central tendencies with outliers_en.vtt
3.8 kB
06 - Descriptive statistics/011 Measures of dispersion (variance, standard deviation).mp4
54 MB
06 - Descriptive statistics/011 Measures of dispersion (variance, standard deviation)_en.srt
26 kB
06 - Descriptive statistics/011 Measures of dispersion (variance, standard deviation)_en.vtt
23 kB
06 - Descriptive statistics/012 Code_ Computing dispersion.mp4
266 MB
06 - Descriptive statistics/012 Code_ Computing dispersion_en.srt
37 kB
06 - Descriptive statistics/012 Code_ Computing dispersion_en.vtt
32 kB
06 - Descriptive statistics/013 Interquartile range (IQR).mp4
9.8 MB
06 - Descriptive statistics/013 Interquartile range (IQR)_en.srt
7.0 kB
06 - Descriptive statistics/013 Interquartile range (IQR)_en.vtt
6.1 kB
06 - Descriptive statistics/014 Code_ IQR.mp4
83 MB
06 - Descriptive statistics/014 Code_ IQR_en.srt
23 kB
06 - Descriptive statistics/014 Code_ IQR_en.vtt
20 kB
06 - Descriptive statistics/015 QQ plots.mp4
16 MB
06 - Descriptive statistics/015 QQ plots_en.srt
10 kB
06 - Descriptive statistics/015 QQ plots_en.vtt
8.9 kB
06 - Descriptive statistics/016 Code_ QQ plots.mp4
90 MB
06 - Descriptive statistics/016 Code_ QQ plots_en.srt
24 kB
06 - Descriptive statistics/016 Code_ QQ plots_en.vtt
20 kB
06 - Descriptive statistics/017 Statistical _moments_.mp4
22 MB
06 - Descriptive statistics/017 Statistical _moments__en.srt
13 kB
06 - Descriptive statistics/017 Statistical _moments__en.vtt
11 kB
06 - Descriptive statistics/018 Histograms part 2_ Number of bins.mp4
24 MB
06 - Descriptive statistics/018 Histograms part 2_ Number of bins_en.srt
14 kB
06 - Descriptive statistics/018 Histograms part 2_ Number of bins_en.vtt
12 kB
06 - Descriptive statistics/019 Code_ Histogram bins.mp4
118 MB
06 - Descriptive statistics/019 Code_ Histogram bins_en.srt
18 kB
06 - Descriptive statistics/019 Code_ Histogram bins_en.vtt
15 kB
06 - Descriptive statistics/020 Violin plots.mp4
6.5 MB
06 - Descriptive statistics/020 Violin plots_en.srt
5.0 kB
06 - Descriptive statistics/020 Violin plots_en.vtt
4.3 kB
06 - Descriptive statistics/021 Code_ violin plots.mp4
105 MB
06 - Descriptive statistics/021 Code_ violin plots_en.srt
15 kB
06 - Descriptive statistics/021 Code_ violin plots_en.vtt
13 kB
06 - Descriptive statistics/022 _Unsupervised learning__ asymmetric violin plots.mp4
17 MB
06 - Descriptive statistics/022 _Unsupervised learning__ asymmetric violin plots_en.srt
3.8 kB
06 - Descriptive statistics/022 _Unsupervised learning__ asymmetric violin plots_en.vtt
3.3 kB
06 - Descriptive statistics/023 Shannon entropy.mp4
33 MB
06 - Descriptive statistics/023 Shannon entropy_en.srt
16 kB
06 - Descriptive statistics/023 Shannon entropy_en.vtt
14 kB
06 - Descriptive statistics/024 Code_ entropy.mp4
97 MB
06 - Descriptive statistics/024 Code_ entropy_en.srt
30 kB
06 - Descriptive statistics/024 Code_ entropy_en.vtt
26 kB
06 - Descriptive statistics/025 _Unsupervised learning__ entropy and number of bins.mp4
8.3 MB
06 - Descriptive statistics/025 _Unsupervised learning__ entropy and number of bins_en.srt
2.0 kB
06 - Descriptive statistics/025 _Unsupervised learning__ entropy and number of bins_en.vtt
1.8 kB
07 - Data normalizations and outliers/001 Garbage in, garbage out (GIGO).mp4
12 MB
07 - Data normalizations and outliers/001 Garbage in, garbage out (GIGO)_en.srt
5.7 kB
07 - Data normalizations and outliers/001 Garbage in, garbage out (GIGO)_en.vtt
5.0 kB
07 - Data normalizations and outliers/002 Z-score standardization.mp4
36 MB
07 - Data normalizations and outliers/002 Z-score standardization_en.srt
14 kB
07 - Data normalizations and outliers/002 Z-score standardization_en.vtt
12 kB
07 - Data normalizations and outliers/003 Code_ z-score.mp4
67 MB
07 - Data normalizations and outliers/003 Code_ z-score_en.srt
19 kB
07 - Data normalizations and outliers/003 Code_ z-score_en.vtt
17 kB
07 - Data normalizations and outliers/004 Min-max scaling.mp4
12 MB
07 - Data normalizations and outliers/004 Min-max scaling_en.srt
7.2 kB
07 - Data normalizations and outliers/004 Min-max scaling_en.vtt
6.3 kB
07 - Data normalizations and outliers/005 Code_ min-max scaling.mp4
40 MB
07 - Data normalizations and outliers/005 Code_ min-max scaling_en.srt
13 kB
07 - Data normalizations and outliers/005 Code_ min-max scaling_en.vtt
11 kB
07 - Data normalizations and outliers/006 _Unsupervised learning__ Invert the min-max scaling.mp4
6.8 MB
07 - Data normalizations and outliers/006 _Unsupervised learning__ Invert the min-max scaling_en.srt
3.6 kB
07 - Data normalizations and outliers/006 _Unsupervised learning__ Invert the min-max scaling_en.vtt
3.2 kB
07 - Data normalizations and outliers/007 What are outliers and why are they dangerous_.mp4
43 MB
07 - Data normalizations and outliers/007 What are outliers and why are they dangerous__en.srt
22 kB
07 - Data normalizations and outliers/007 What are outliers and why are they dangerous__en.vtt
18 kB
07 - Data normalizations and outliers/008 Removing outliers_ z-score method.mp4
34 MB
07 - Data normalizations and outliers/008 Removing outliers_ z-score method_en.srt
14 kB
07 - Data normalizations and outliers/008 Removing outliers_ z-score method_en.vtt
12 kB
07 - Data normalizations and outliers/009 The modified z-score method.mp4
9.6 MB
07 - Data normalizations and outliers/009 The modified z-score method_en.srt
5.9 kB
07 - Data normalizations and outliers/009 The modified z-score method_en.vtt
5.1 kB
07 - Data normalizations and outliers/010 Code_ z-score for outlier removal.mp4
137 MB
07 - Data normalizations and outliers/010 Code_ z-score for outlier removal_en.srt
34 kB
07 - Data normalizations and outliers/010 Code_ z-score for outlier removal_en.vtt
29 kB
07 - Data normalizations and outliers/011 _Unsupervised learning__ z vs. modified-z.mp4
9.0 MB
07 - Data normalizations and outliers/011 _Unsupervised learning__ z vs. modified-z_en.srt
3.8 kB
07 - Data normalizations and outliers/011 _Unsupervised learning__ z vs. modified-z_en.vtt
3.4 kB
07 - Data normalizations and outliers/012 Multivariate outlier detection.mp4
25 MB
07 - Data normalizations and outliers/012 Multivariate outlier detection_en.srt
14 kB
07 - Data normalizations and outliers/012 Multivariate outlier detection_en.vtt
12 kB
07 - Data normalizations and outliers/013 Code_ Euclidean distance for outlier removal.mp4
44 MB
07 - Data normalizations and outliers/013 Code_ Euclidean distance for outlier removal_en.srt
13 kB
07 - Data normalizations and outliers/013 Code_ Euclidean distance for outlier removal_en.vtt
11 kB
07 - Data normalizations and outliers/014 Removing outliers by data trimming.mp4
17 MB
07 - Data normalizations and outliers/014 Removing outliers by data trimming_en.srt
8.5 kB
07 - Data normalizations and outliers/014 Removing outliers by data trimming_en.vtt
7.4 kB
07 - Data normalizations and outliers/015 Code_ Data trimming to remove outliers.mp4
65 MB
07 - Data normalizations and outliers/015 Code_ Data trimming to remove outliers_en.srt
16 kB
07 - Data normalizations and outliers/015 Code_ Data trimming to remove outliers_en.vtt
14 kB
07 - Data normalizations and outliers/016 Non-parametric solutions to outliers.mp4
23 MB
07 - Data normalizations and outliers/016 Non-parametric solutions to outliers_en.srt
6.3 kB
07 - Data normalizations and outliers/016 Non-parametric solutions to outliers_en.vtt
5.6 kB
07 - Data normalizations and outliers/017 Nonlinear data transformations.mp4
34 MB
07 - Data normalizations and outliers/017 Nonlinear data transformations_en.srt
20 kB
07 - Data normalizations and outliers/017 Nonlinear data transformations_en.vtt
17 kB
07 - Data normalizations and outliers/018 An outlier lecture on personal accountability.mp4
18 MB
07 - Data normalizations and outliers/018 An outlier lecture on personal accountability_en.srt
4.1 kB
07 - Data normalizations and outliers/018 An outlier lecture on personal accountability_en.vtt
3.6 kB
08 - Probability theory/001 What is probability_.mp4
41 MB
08 - Probability theory/001 What is probability__en.srt
18 kB
08 - Probability theory/001 What is probability__en.vtt
16 kB
08 - Probability theory/002 Probability vs. proportion.mp4
38 MB
08 - Probability theory/002 Probability vs. proportion_en.srt
14 kB
08 - Probability theory/002 Probability vs. proportion_en.vtt
12 kB
08 - Probability theory/003 Computing probabilities.mp4
38 MB
08 - Probability theory/003 Computing probabilities_en.srt
15 kB
08 - Probability theory/003 Computing probabilities_en.vtt
13 kB
08 - Probability theory/004 Code_ compute probabilities.mp4
148 MB
08 - Probability theory/004 Code_ compute probabilities_en.srt
22 kB
08 - Probability theory/004 Code_ compute probabilities_en.vtt
19 kB
08 - Probability theory/005 Probability and odds.mp4
12 MB
08 - Probability theory/005 Probability and odds_en.srt
6.9 kB
08 - Probability theory/005 Probability and odds_en.vtt
6.0 kB
08 - Probability theory/006 _Unsupervised learning__ probabilities of odds-space.mp4
5.9 MB
08 - Probability theory/006 _Unsupervised learning__ probabilities of odds-space_en.srt
3.1 kB
08 - Probability theory/006 _Unsupervised learning__ probabilities of odds-space_en.vtt
2.8 kB
08 - Probability theory/007 Probability mass vs. density.mp4
134 MB
08 - Probability theory/007 Probability mass vs. density_en.srt
18 kB
08 - Probability theory/007 Probability mass vs. density_en.vtt
16 kB
08 - Probability theory/008 Code_ compute probability mass functions.mp4
66 MB
08 - Probability theory/008 Code_ compute probability mass functions_en.srt
16 kB
08 - Probability theory/008 Code_ compute probability mass functions_en.vtt
14 kB
08 - Probability theory/009 Cumulative distribution functions.mp4
45 MB
08 - Probability theory/009 Cumulative distribution functions_en.srt
20 kB
08 - Probability theory/009 Cumulative distribution functions_en.vtt
18 kB
08 - Probability theory/010 Code_ cdfs and pdfs.mp4
96 MB
08 - Probability theory/010 Code_ cdfs and pdfs_en.srt
14 kB
08 - Probability theory/010 Code_ cdfs and pdfs_en.vtt
13 kB
08 - Probability theory/011 _Unsupervised learning__ cdf's for various distributions.mp4
9.3 MB
08 - Probability theory/011 _Unsupervised learning__ cdf's for various distributions_en.srt
3.3 kB
08 - Probability theory/011 _Unsupervised learning__ cdf's for various distributions_en.vtt
2.9 kB
08 - Probability theory/012 Creating sample estimate distributions.mp4
125 MB
08 - Probability theory/012 Creating sample estimate distributions_en.srt
28 kB
08 - Probability theory/012 Creating sample estimate distributions_en.vtt
24 kB
08 - Probability theory/013 Monte Carlo sampling.mp4
8.8 MB
08 - Probability theory/013 Monte Carlo sampling_en.srt
3.8 kB
08 - Probability theory/013 Monte Carlo sampling_en.vtt
3.4 kB
08 - Probability theory/014 Sampling variability, noise, and other annoyances.mp4
106 MB
08 - Probability theory/014 Sampling variability, noise, and other annoyances_en.srt
13 kB
08 - Probability theory/014 Sampling variability, noise, and other annoyances_en.vtt
11 kB
08 - Probability theory/015 Code_ sampling variability.mp4
155 MB
08 - Probability theory/015 Code_ sampling variability_en.srt
38 kB
08 - Probability theory/015 Code_ sampling variability_en.vtt
33 kB
08 - Probability theory/016 Expected value.mp4
60 MB
08 - Probability theory/016 Expected value_en.srt
15 kB
08 - Probability theory/016 Expected value_en.vtt
13 kB
08 - Probability theory/017 Conditional probability.mp4
86 MB
08 - Probability theory/017 Conditional probability_en.srt
19 kB
08 - Probability theory/017 Conditional probability_en.vtt
16 kB
08 - Probability theory/018 Code_ conditional probabilities.mp4
115 MB
08 - Probability theory/018 Code_ conditional probabilities_en.srt
30 kB
08 - Probability theory/018 Code_ conditional probabilities_en.vtt
25 kB
08 - Probability theory/019 Tree diagrams for conditional probabilities.mp4
14 MB
08 - Probability theory/019 Tree diagrams for conditional probabilities_en.srt
9.9 kB
08 - Probability theory/019 Tree diagrams for conditional probabilities_en.vtt
8.6 kB
08 - Probability theory/020 The Law of Large Numbers.mp4
41 MB
08 - Probability theory/020 The Law of Large Numbers_en.srt
14 kB
08 - Probability theory/020 The Law of Large Numbers_en.vtt
12 kB
08 - Probability theory/021 Code_ Law of Large Numbers in action.mp4
166 MB
08 - Probability theory/021 Code_ Law of Large Numbers in action_en.srt
28 kB
08 - Probability theory/021 Code_ Law of Large Numbers in action_en.vtt
24 kB
08 - Probability theory/022 The Central Limit Theorem.mp4
27 MB
08 - Probability theory/022 The Central Limit Theorem_en.srt
16 kB
08 - Probability theory/022 The Central Limit Theorem_en.vtt
14 kB
08 - Probability theory/023 Code_ the CLT in action.mp4
93 MB
08 - Probability theory/023 Code_ the CLT in action_en.srt
24 kB
08 - Probability theory/023 Code_ the CLT in action_en.vtt
20 kB
08 - Probability theory/024 _Unsupervised learning__ Averaging pairs of numbers.mp4
9.5 MB
08 - Probability theory/024 _Unsupervised learning__ Averaging pairs of numbers_en.srt
3.2 kB
08 - Probability theory/024 _Unsupervised learning__ Averaging pairs of numbers_en.vtt
2.8 kB
09 - Hypothesis testing/001 IVs, DVs, models, and other stats lingo.mp4
91 MB
09 - Hypothesis testing/001 IVs, DVs, models, and other stats lingo_en.srt
24 kB
09 - Hypothesis testing/001 IVs, DVs, models, and other stats lingo_en.vtt
21 kB
09 - Hypothesis testing/002 What is an hypothesis and how do you specify one_.mp4
49 MB
09 - Hypothesis testing/002 What is an hypothesis and how do you specify one__en.srt
23 kB
09 - Hypothesis testing/002 What is an hypothesis and how do you specify one__en.vtt
20 kB
09 - Hypothesis testing/003 Sample distributions under null and alternative hypotheses.mp4
44 MB
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10 - The t-test family/001 Purpose and interpretation of the t-test.mp4
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10 - The t-test family/004 _Unsupervised learning__ The role of variance.mp4
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10 - The t-test family/008 Wilcoxon signed-rank (nonparametric t-test).mp4
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10 - The t-test family/010 Mann-Whitney U test (nonparametric t-test).mp4
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10 - The t-test family/012 Permutation testing for t-test significance.mp4
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11 - Confidence intervals on parameters/001 What are confidence intervals and why do we need them_.mp4
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11 - Confidence intervals on parameters/004 Confidence intervals via bootstrapping (resampling).mp4
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12 - Correlation/001 Motivation and description of correlation.mp4
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12 - Correlation/002 Covariance and correlation_ formulas.mp4
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12 - Correlation/009 Partial correlation.mp4
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12 - Correlation/011 The problem with Pearson.mp4
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12 - Correlation/012 Nonparametric correlation_ Spearman rank.mp4
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12 - Correlation/013 Fisher-Z transformation for correlations.mp4
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12 - Correlation/014 Code_ Spearman correlation and Fisher-Z.mp4
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12 - Correlation/016 _Unsupervised learning__ confidence interval on correlation.mp4
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12 - Correlation/017 Kendall's correlation for ordinal data.mp4
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12 - Correlation/018 Code_ Kendall correlation.mp4
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12 - Correlation/019 _Unsupervised learning__ Does Kendall vs. Pearson matter_.mp4
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12 - Correlation/020 The subgroups correlation paradox.mp4
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12 - Correlation/021 Cosine similarity.mp4
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12 - Correlation/022 Code_ Cosine similarity vs. Pearson correlation.mp4
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12 - Correlation/[Tutorialsplanet.NET].url
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13 - Analysis of Variance (ANOVA)/001 ANOVA intro, part1.mp4
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13 - Analysis of Variance (ANOVA)/003 Sum of squares.mp4
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13 - Analysis of Variance (ANOVA)/004 The F-test and the ANOVA table.mp4
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13 - Analysis of Variance (ANOVA)/005 The omnibus F-test and post-hoc comparisons.mp4
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13 - Analysis of Variance (ANOVA)/006 The two-way ANOVA.mp4
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13 - Analysis of Variance (ANOVA)/007 One-way ANOVA example.mp4
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14 - Regression/001 Introduction to GLM _ regression.mp4
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14 - Regression/002 Least-squares solution to the GLM.mp4
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14 - Regression/003 Evaluating regression models_ R2 and F.mp4
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14 - Regression/004 Simple regression.mp4
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14 - Regression/007 Multiple regression.mp4
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14 - Regression/008 Standardizing regression coefficients.mp4
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14 - Regression/009 Code_ Multiple regression.mp4
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14 - Regression/010 Polynomial regression models.mp4
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14 - Regression/013 Logistic regression.mp4
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14 - Regression/015 Under- and over-fitting.mp4
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14 - Regression/017 Comparing _nested_ models.mp4
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14 - Regression/018 What to do about missing data.mp4
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15 - Statistical power and sample sizes/001 What is statistical power and why is it important_.mp4
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15 - Statistical power and sample sizes/002 Estimating statistical power and sample size.mp4
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15 - Statistical power and sample sizes/003 Compute power and sample size using G_Power.mp4
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16 - Clustering and dimension-reduction/001 K-means clustering.mp4
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16 - Clustering and dimension-reduction/005 Clustering via dbscan.mp4
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16 - Clustering and dimension-reduction/008 K-nearest neighbor classification.mp4
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16 - Clustering and dimension-reduction/010 Principal components analysis (PCA).mp4
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16 - Clustering and dimension-reduction/012 _Unsupervised learning__ K-means on PC data.mp4
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16 - Clustering and dimension-reduction/013 Independent components analysis (ICA).mp4
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17 - Signal detection theory/001 The two perspectives of the world.mp4
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17 - Signal detection theory/007 Receiver operating characteristics (ROC).mp4
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17 - Signal detection theory/007 Receiver operating characteristics (ROC)_en.srt
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17 - Signal detection theory/007 Receiver operating characteristics (ROC)_en.vtt
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17 - Signal detection theory/008 Code_ ROC curves.mp4
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17 - Signal detection theory/008 Code_ ROC curves_en.srt
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17 - Signal detection theory/008 Code_ ROC curves_en.vtt
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17 - Signal detection theory/009 _Unsupervised learning__ Make this plot look nicer_.mp4
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17 - Signal detection theory/009 _Unsupervised learning__ Make this plot look nicer__en.srt
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17 - Signal detection theory/009 _Unsupervised learning__ Make this plot look nicer__en.vtt
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18 - A real-world data journey/001 Note about the code for this section.html
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18 - A real-world data journey/002 Introduction.mp4
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18 - A real-world data journey/002 Introduction_en.srt
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18 - A real-world data journey/002 Introduction_en.vtt
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18 - A real-world data journey/003 MATLAB_ Import and clean the marriage data.mp4
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18 - A real-world data journey/003 MATLAB_ Import and clean the marriage data_en.srt
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18 - A real-world data journey/003 MATLAB_ Import and clean the marriage data_en.vtt
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18 - A real-world data journey/004 MATLAB_ Import the divorce data.mp4
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18 - A real-world data journey/004 MATLAB_ Import the divorce data_en.srt
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18 - A real-world data journey/004 MATLAB_ Import the divorce data_en.vtt
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18 - A real-world data journey/005 MATLAB_ More data visualizations.mp4
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18 - A real-world data journey/005 MATLAB_ More data visualizations_en.srt
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18 - A real-world data journey/005 MATLAB_ More data visualizations_en.vtt
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18 - A real-world data journey/006 MATLAB_ Inferential statistics.mp4
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18 - A real-world data journey/006 MATLAB_ Inferential statistics_en.srt
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18 - A real-world data journey/006 MATLAB_ Inferential statistics_en.vtt
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18 - A real-world data journey/007 Python_ Import and clean the marriage data.mp4
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18 - A real-world data journey/007 Python_ Import and clean the marriage data_en.srt
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18 - A real-world data journey/007 Python_ Import and clean the marriage data_en.vtt
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18 - A real-world data journey/008 Python_ Import the divorce data.mp4
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18 - A real-world data journey/008 Python_ Import the divorce data_en.srt
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18 - A real-world data journey/008 Python_ Import the divorce data_en.vtt
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18 - A real-world data journey/009 Python_ Inferential statistics.mp4
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18 - A real-world data journey/009 Python_ Inferential statistics_en.srt
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18 - A real-world data journey/009 Python_ Inferential statistics_en.vtt
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18 - A real-world data journey/010 Take-home messages.mp4
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18 - A real-world data journey/010 Take-home messages_en.srt
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18 - A real-world data journey/010 Take-home messages_en.vtt
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18 - A real-world data journey/35855730-state-marriage-rates-90-95-99-19.xlsx
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18 - A real-world data journey/35855734-state-divorce-rates-90-95-99-19.xlsx
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19 - Bonus section/001 About deep learning.html
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19 - Bonus section/002 Bonus content.html
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19 - Bonus section/[Tutorialsplanet.NET].url
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[Tutorialsplanet.NET].url
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