Udemy - Probability - Stats - The Foundations Of Machine Learning

Files:

• Get Bonus Downloads Here.url (0.2 KB)
~Get Your Files Here ! 1 - Diving in with code
• 1 - Code env setup and Python crash course.mp4 (164.6 MB)
• 2 - Getting started with code Feel of data.mp4 (84.4 MB)
• 3 - Foundations data types and representing data English.srt (34.9 KB)
• 3 - Foundations data types and representing data.mp4 (145.1 MB)
• 4 - Practical note onehot vector encoding English.srt (8.0 KB)
• 4 - Practical note onehot vector encoding.mp4 (29.2 MB)
• 5 - Exploring data types in code English.srt (21.5 KB)
• 5 - Exploring data types in code.mp4 (139.9 MB)
• 6 - Central tendency mean median mode.mp4 (118.5 MB)
• 7 - Section Review Tasks.html (2.2 KB)
__MACOSX
• _pdfs (0.2 KB)
• _prob-cs (0.2 KB)
pdfs
• _01-intro-to-data.pdf (0.3 KB)
• _02-averages.pdf (0.3 KB)
• _03-variance.pdf (0.3 KB)
• _05-probability.pdf (0.2 KB)
• _06-counting.pdf (0.2 KB)
• _06-prob-rules.pdf (0.3 KB)
• _07-bayes-rule.pdf (0.3 KB)
• _08-random-variables.pdf (0.2 KB)
• _09-distributions.pdf (0.2 KB)
• _10-continuous-distributions.pdf (0.2 KB)
• _11-expected-values.pdf (0.2 KB)
• _12-entropy.pdf (0.2 KB)
• _13-mcmc.pdf (0.2 KB)
• _14-kl-divergence.pdf (0.2 KB)
prob-cs
• _.DS_Store (0.1 KB)
• _.ipynb_checkpoints (0.2 KB)
• _00-basic-python-crash-course.ipynb (0.2 KB)
• _00-nhanes_data_basics.ipynb (0.2 KB)
• _01-data-types.ipynb (0.2 KB)
• _02-studying-variables.ipynb (0.2 KB)
• _03-dispersion.ipynb (0.2 KB)
• _04-coin-flips.ipynb (0.2 KB)
• _05-spam-detection.ipynb (0.2 KB)
• _06-distributions.ipynb (0.2 KB)
• _06-joints-and-marginals.ipynb (0.2 KB)
• _07-decision-tree.ipynb (0.2 KB)
• _08-bayesian-inference.ipynb (0.2 KB)
• _data (0.2 KB)
data
• _.ipynb_checkpoints (0.2 KB)
• _nhanes_2015_2016.csv (0.2 KB)
• _sleep_data.csv (0.2 KB)
• _zoo.data (0.2 KB)
• _zoo.names (0.2 KB)
ipynb_checkpoints
• _nhanes_2015_2016-checkpoint.csv (0.2 KB)
• _sleep_data-checkpoint.csv (0.2 KB)
• _zoo-checkpoint.data (0.2 KB)
ipynb_checkpoints
• _00-basic-python-crash-course-checkpoint.ipynb (0.2 KB)
• _00-nhanes_data_basics-checkpoint.ipynb (0.2 KB)
• _01-data-types-checkpoint.ipynb (0.2 KB)
• _02-studying-variables-checkpoint.ipynb (0.2 KB)
• _03-dispersion-checkpoint.ipynb (0.2 KB)
• _04-coin-flips-checkpoint.ipynb (0.2 KB)
• _05-spam-detection-checkpoint.ipynb (0.2 KB)
• _06-distributions-checkpoint.ipynb (0.2 KB)
• _06-joints-and-marginals-checkpoint.ipynb (0.2 KB)
• _07-decision-tree-checkpoint.ipynb (0.2 KB)
• _08-bayesian-inference-checkpoint.ipynb (0.2 KB)
• _Untitled-checkpoint.ipynb (0.2 KB)
pdfs
• 01-intro-to-data.pdf (2.5 MB)
• 02-averages.pdf (1.0 MB)
• 03-variance.pdf (1,001.3 KB)
• 05-probability.pdf (4.7 MB)
• 06-counting.pdf (5.5 MB)
• 06-prob-rules.pdf (6.7 MB)
• 07-bayes-rule.pdf (6.2 MB)
• 08-random-variables.pdf (5.9 MB)
• 09-distributions.pdf (3.4 MB)
• 10-continuous-distributions.pdf (5.7 MB)
• 11-expected-values.pdf (1.6 MB)
• 12-entropy.pdf (5.0 MB)
• 13-mcmc.pdf (3.1 MB)
• 14-kl-divergence.pdf (2.7 MB)
prob-cs
• 00-basic-python-crash-course.ipynb (46.4 KB)
• 00-nhanes_data_basics.ipynb (115.2 KB)
• 01-data-types.ipynb (9.0 KB)
• 02-studying-variables.ipynb (296.5 KB)
• 03-dispersion.ipynb (87.0 KB)
• 04-coin-flips.ipynb (148.4 KB)
• 05-spam-detection.ipynb (15.9 KB)
• 06-distributions.ipynb (295.6 KB)
• 06-joints-and-marginals.ipynb (258.6 KB)
• 07-decision-tree.ipynb (30.0 KB)
• 08-bayesian-inference.ipynb (2.7 KB)
• DS_Store (6.0 KB)
data ipynb_checkpoints
• nhanes_2015_2016-checkpoint.csv (744.5 KB)
• sleep_data-checkpoint.csv (280.6 KB)
• zoo-checkpoint.data (4.0 KB)
• nhanes_2015_2016.csv (744.5 KB)
• sleep_data.csv (280.6 KB)
• zoo.data (4.0 KB)
• zoo.names (2.5 KB)
ipynb_checkpoints
• 00-basic-python-crash-course-checkpoint.ipynb (46.4 KB)
• 00-nhanes_data_basics-checkpoint.ipynb (115.2 KB)
• 01-data-types-checkpoint.ipynb (2.8 KB)
• 02-studying-variables-checkpoint.ipynb (296.5 KB)
• 03-dispersion-checkpoint.ipynb (7.1 KB)
• 04-coin-flips-checkpoint.ipynb (9.1 KB)
• 05-spam-detection-checkpoint.ipynb (14.2 KB)
• 06-distributions-checkpoint.ipynb (51.1 KB)
• 06-joints-and-marginals-checkpoint.ipynb (7.2 KB)
• 07-decision-tree-checkpoint.ipynb (30.0 KB)
• 08-bayesian-inference-checkpoint.ipynb (2.7 KB)
• Untitled-checkpoint.ipynb (0.1 KB)
2 - Measures of Spread
• 10 - Section Review Tasks.html (0.5 KB)
• 8 - Dispersion and spread in data variance standard deviation.mp4 (43.0 MB)
• 9 - Dispersion exploration through code English.srt (16.8 KB)
• 9 - Dispersion exploration through code.mp4 (65.9 MB)
3 - Applications and Rules for Probability
• 11 - Intro to uncertainty probability intuition.mp4 (57.5 MB)
• 12 - Simulating coin flips for probability.mp4 (124.9 MB)
• 13 - Conditional probability the most important concept in stats English.srt (34.4 KB)
• 13 - Conditional probability the most important concept in stats.mp4 (113.5 MB)
• 14 - Applying conditional probability Bayes rule English.srt (15.7 KB)
• 14 - Applying conditional probability Bayes rule.mp4 (43.1 MB)
• 15 - Application of Bayes rule in real world Spam detection English.srt (13.4 KB)
• 15 - Application of Bayes rule in real world Spam detection.mp4 (61.4 MB)
• 16 - Spam detection implementation issues English.srt (16.9 KB)
• 16 - Spam detection implementation issues.mp4 (124.3 MB)
• 17 - Section Review Tasks.html (4.1 KB)
4 - Counting
• 18 - Rules for counting Mostly optional English.srt (25.3 KB)
• 18 - Rules for counting Mostly optional.mp4 (93.9 MB)
• 19 - Section Review Tasks.html (1.1 KB)
5 - Random Variables Rationale and Applications
• 20 - Quantifying events random variables.mp4 (44.0 MB)
• 21 - Two random variables joint probabilities English.srt (20.9 KB)
• 21 - Two random variables joint probabilities.mp4 (48.9 MB)
• 22 - Distributions rationale and importance English.srt (29.7 KB)
• 22 - Distributions rationale and importance.mp4 (116.2 MB)
• 23 - Discrete distributions through code English.srt (8.7 KB)
• 23 - Discrete distributions through code.mp4 (24.3 MB)
• 24 - Continuous distributions probability densities English.srt (35.1 KB)
• 24 - Continuous distributions probability densities.mp4 (87.9 MB)
• 25 - Continuous distributions code English.srt (9.2 KB)
• 25 - Continuous distributions code.mp4 (28.1 MB)
• 26 - Case study sleep analysis structure and code English.srt (31.5 KB)
• 26 - Case study sleep analysis structure and code.mp4 (163.5 MB)
• 27 - Section Review Tasks.html (0.9 KB)
6 - Visualization in Intuition Building
• 28 - Visualizing joint distributions the road to ML success.mp4 (87.2 MB)
• 29 - Dependence and variance of two random variables English.srt (18.6 KB)
• 29 - Dependence and variance of two random variables.mp4 (61.2 MB)
• 30 - Section Review Tasks.html (0.8 KB)
7 - Applications to the Real World
• 31 - Expected values decision making through probabilities English.srt (11.4 KB)
• 31 - Expected values decision making through probabilities.mp4 (18.7 MB)
• 32 - Entropy The most important application of expected values.mp4 (86.5 MB)
• 33 - Applying entropy coding decision trees for machine learning English.srt (47.0 KB)
• 33 - Applying entropy coding decision trees for machine learning.mp4 (141.5 MB)
• 34 - Foundations of Bayesian inference English.srt (19.9 KB)
• 34 - Foundations of Bayesian inference.mp4 (26.6 MB)
• 35 - Bayesian inference code through PyMC3 English.srt (11.1 KB)
• 35 - Bayesian inference code through PyMC3.mp4 (57.9 MB)
• 36 - Section Review Tasks.html (2.1 KB)
8 - Extra Resources
• 37 - Bonus Lecture.html (4.8 KB)
• Bonus Resources.txt (0.4 KB)