Udemy - Machine Learning & Data Science The Complete Visual Guide (6.2025)

Creation Time	Aug. 11, 2025, 6 a.m.
Last Access Time	Dec. 7, 2025, 5:14 p.m.
File Size	1.9 GB
Keywords	Complete Science - Udemy Machine 2025 Visual Learning 6 The Data Guide
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Total Files	380
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04. Preliminary Data QA/9. CASE STUDY Preliminary QA.mp4 152.6 MB
18. Clustering & Segmentation/6. CASE STUDY K-Means.mp4 91.9 MB
13. Regression Modeling 101/8. CASE STUDY Non-Linear Regression.mp4 82.7 MB
09. Classification Models/4. CASE STUDY KNN.mp4 78.0 MB
15. Time-Series Forecasting/6. CASE STUDY Seasonality with One-Hot Encoding.mp4 67.0 MB
15. Time-Series Forecasting/8. CASE STUDY Seasonality with Linear Trend.mp4 59.7 MB
15. Time-Series Forecasting/14. CASE STUDY Intervention Analysis.mp4 58.6 MB
20. Outlier Detection/5. CASE STUDY Cross-Sectional Outlier.mp4 57.4 MB
19. Association Mining & Basket Analysis/8. CASE STUDY Apriori.mp4 48.0 MB
05. Univariate Profiling/10. CASE STUDY Normal Distribution.mp4 46.1 MB
09. Classification Models/21. CASE STUDY Logistic Regression.mp4 39.3 MB
09. Classification Models/14. CASE STUDY Decision Trees.mp4 39.0 MB
09. Classification Models/25. CASE STUDY Sentiment Analysis.mp4 38.7 MB
06. Multivariate Profiling/13. CASE STUDY Correlation.mp4 35.7 MB
06. Multivariate Profiling/3. CASE STUDY Heat Maps.mp4 29.7 MB
13. Regression Modeling 101/5. CASE STUDY Univariate Linear Regression.mp4 29.1 MB
13. Regression Modeling 101/3. Least Squared Error.mp4 28.3 MB
15. Time-Series Forecasting/10. CASE STUDY Smoothing.mp4 24.1 MB
05. Univariate Profiling/8. CASE STUDY Histograms.mp4 23.5 MB
09. Classification Models/8. CASE STUDY Naïve Bayes.mp4 22.3 MB
13. Regression Modeling 101/6. Multiple Linear Regression.mp4 19.3 MB
15. Time-Series Forecasting/12. CASE STUDY Non-Linear Trend.mp4 18.0 MB
06. Multivariate Profiling/1. Introduction.mp4 17.0 MB
15. Time-Series Forecasting/4. CASE STUDY Seasonality with ACF.mp4 16.9 MB
01. Getting Started/3. Visual Guide to Machine Learning.pdf 16.4 MB
18. Clustering & Segmentation/3. Intro to K-Means.mp4 16.3 MB
19. Association Mining & Basket Analysis/10. CASE STUDY Markov Chains.mp4 16.0 MB
01. Getting Started/1. Course Structure & Outline.mp4 15.6 MB
14. Model Diagnostics/4. Mean Error Metrics (MSE, MAE, MAPE).mp4 12.8 MB
13. Regression Modeling 101/2. Linear Relationships.mp4 11.9 MB
19. Association Mining & Basket Analysis/9. Markov Chains.mp4 11.5 MB
19. Association Mining & Basket Analysis/4. Basket Analysis Examples.mp4 11.2 MB
09. Classification Models/7. Naïve Bayes Conditional Probability.mp4 11.1 MB
05. Univariate Profiling/7. Histograms & Kernel Densities.mp4 10.6 MB
09. Classification Models/12. Decision Tree Examples.mp4 10.5 MB
14. Model Diagnostics/3. R-Squared.mp4 10.4 MB
14. Model Diagnostics/11. RECAP Sample Model Output.mp4 10.1 MB
09. Classification Models/19. The Likelihood Function.mp4 10.0 MB
10. Model Selection & Tuning/7. Multi-class Scoring.mp4 9.3 MB
09. Classification Models/11. Entropy & Information Gain.mp4 9.3 MB
09. Classification Models/24. Bag of Words Analysis.mp4 9.3 MB
14. Model Diagnostics/8. T-Values & P-Values.mp4 9.2 MB
08. Intro to Classification/1. Supervised vs. Unsupervised Learning.mp4 8.9 MB
09. Classification Models/3. KNN Examples.mp4 8.4 MB
04. Preliminary Data QA/4. Empty Values.mp4 8.2 MB
19. Association Mining & Basket Analysis/6. Infrequent Itemsets.mp4 8.2 MB
20. Outlier Detection/4. Cross-Sectional Outlier Example.mp4 8.1 MB
13. Regression Modeling 101/7. Non-Linear Regression.mp4 8.0 MB
08. Intro to Classification/4. Classification 101.mp4 8.0 MB
20. Outlier Detection/7. Time-Series Outlier Example.mp4 7.9 MB
14. Model Diagnostics/10. Variance Inflation Factor.mp4 7.9 MB
08. Intro to Classification/8. Overfitting.mp4 7.7 MB
08. Intro to Classification/6. Feature Engineering.mp4 7.5 MB
05. Univariate Profiling/5. Categorical Distributions.mp4 7.5 MB
06. Multivariate Profiling/2. Categorical-Categorical.mp4 7.4 MB
10. Model Selection & Tuning/3. Imbalanced Classes.mp4 7.1 MB
06. Multivariate Profiling/10. Correlation.mp4 7.0 MB
08. Intro to Classification/3. RECAP Key Concepts.mp4 7.0 MB
14. Model Diagnostics/7. F-Significance.mp4 6.9 MB
09. Classification Models/17. False Positives vs. False Negatives.mp4 6.9 MB
15. Time-Series Forecasting/13. Intervention Analysis.mp4 6.7 MB
10. Model Selection & Tuning/2. Hyperparameters.mp4 6.5 MB
21. Dimensionality Reduction/5. Interpreting Components.mp4 6.4 MB
12. Intro to Regression/4. Feature Engineering for Regression.mp4 6.3 MB
18. Clustering & Segmentation/7. Intro to Hierarchical Clustering.mp4 6.3 MB
21. Dimensionality Reduction/4. PCA Example.mp4 6.2 MB
12. Intro to Regression/3. Regression 101.mp4 6.1 MB
06. Multivariate Profiling/5. Multivariate Kernel Densities.mp4 6.1 MB
21. Dimensionality Reduction/2. Dimensionality Reduction Basics.mp4 6.0 MB
02. Intro to the ML Landscape/2. When is ML the right fit.mp4 6.0 MB
21. Dimensionality Reduction/6. Scree Plots.mp4 5.9 MB
08. Intro to Classification/5. Classification Workflow.mp4 5.9 MB
04. Preliminary Data QA/3. Variable Types.mp4 5.9 MB
09. Classification Models/20. Multivariate Logistic Regression.mp4 5.8 MB
05. Univariate Profiling/16. Variance.mp4 5.8 MB
04. Preliminary Data QA/1. Introduction.mp4 5.7 MB
09. Classification Models/10. Decision Trees Entropy 101.mp4 5.7 MB
05. Univariate Profiling/12. Mode.mp4 5.7 MB
12. Intro to Regression/2. RECAP Key Concepts.mp4 5.6 MB
06. Multivariate Profiling/12. Visualizing Third Dimension.mp4 5.4 MB
02. Intro to the ML Landscape/3. The Machine Learning Process.mp4 5.4 MB
14. Model Diagnostics/5. Homoskedasticity.mp4 5.4 MB
04. Preliminary Data QA/8. Table Structure.mp4 5.3 MB
06. Multivariate Profiling/4. Categorical-Numerical.mp4 5.3 MB
15. Time-Series Forecasting/7. Linear Trending.mp4 5.3 MB
06. Multivariate Profiling/8. Limitations of Categorical Distributions.mp4 5.2 MB
05. Univariate Profiling/9. Normal Distribution.mp4 5.1 MB
18. Clustering & Segmentation/4. WSS & Elbow Plots.mp4 5.1 MB
09. Classification Models/16. Logistic Regression Example.mp4 5.1 MB
09. Classification Models/22. Intro to Sentiment Analysis.mp4 5.1 MB
15. Time-Series Forecasting/3. Auto Correlation Function.mp4 5.1 MB
10. Model Selection & Tuning/5. Accuracy, Precision & Recall.mp4 4.9 MB
04. Preliminary Data QA/7. Left & Right Censored Data.mp4 4.9 MB
20. Outlier Detection/3. Cross-Sectional Outliers.mp4 4.9 MB
05. Univariate Profiling/4. Nominal vs. Ordinal.mp4 4.8 MB
15. Time-Series Forecasting/5. One-Hot Encoding.mp4 4.8 MB
15. Time-Series Forecasting/1. Intro to Forecasting.mp4 4.7 MB
10. Model Selection & Tuning/4. Confusion Matrix.mp4 4.7 MB
10. Model Selection & Tuning/6. Multi-class Confusion Matrix.mp4 4.7 MB
01. Getting Started/3. Maven_ML_Demos.xlsx 4.5 MB
05. Univariate Profiling/1. Introduction.mp4 4.5 MB
20. Outlier Detection/2. Outlier Detection Basics.mp4 4.5 MB
01. Getting Started/3. Maven_ML_Demos_COMPLETE.xlsx 4.4 MB
18. Clustering & Segmentation/2. Clustering Basics.mp4 4.4 MB
06. Multivariate Profiling/11. Correlation vs. Causation.mp4 4.4 MB
12. Intro to Regression/1. Supervised vs. Unsupervised Learning.mp4 4.4 MB
02. Intro to the ML Landscape/1. Intro to Machine Learning.mp4 4.4 MB
09. Classification Models/15. Intro to Logistic Regression.mp4 4.4 MB
01. Getting Started/4. Setting Expectations.mp4 4.3 MB
18. Clustering & Segmentation/9. Hierarchical Clustering FAQs.mp4 4.3 MB
17. Intro to Unsupervised ML/1. Supervised vs. Unsupervised Learning.mp4 4.3 MB
18. Clustering & Segmentation/8. Anatomy of a Dendrogram.mp4 4.2 MB
07. PART 2 Classification Modeling/1. Part 2 Classification Modeling.mp4 4.2 MB
09. Classification Models/23. Cleaning Text Data.mp4 4.2 MB
09. Classification Models/9. Intro to Decision Trees.mp4 4.1 MB
15. Time-Series Forecasting/9. Smoothing.mp4 4.1 MB
09. Classification Models/6. Naïve Bayes Frequency Tables.mp4 4.1 MB
17. Intro to Unsupervised ML/3. Unsupervised ML Workflow.mp4 4.0 MB
03. PART 1 QA & Data Profiling/1. Part 1 QA & Data Profiling.mp4 4.0 MB
19. Association Mining & Basket Analysis/3. The Apriori Algorithm.mp4 3.9 MB
20. Outlier Detection/6. Time-Series Outliers.mp4 3.9 MB
05. Univariate Profiling/13. Mean.mp4 3.9 MB
08. Intro to Classification/2. Classification vs. Regression.mp4 3.8 MB
04. Preliminary Data QA/6. Count Calculations.mp4 3.8 MB
05. Univariate Profiling/6. Numerical Variables.mp4 3.8 MB
10. Model Selection & Tuning/8. Model Selection.mp4 3.8 MB
05. Univariate Profiling/3. Discretization.mp4 3.8 MB
05. Univariate Profiling/19. BEST PRACTICES Univariate Profiling.mp4 3.7 MB
08. Intro to Classification/7. Data Splitting.mp4 3.6 MB
19. Association Mining & Basket Analysis/7. Multiple Item Sets.mp4 3.6 MB
19. Association Mining & Basket Analysis/11. KEY TAKEAWAYS Association Mining.mp4 3.6 MB
09. Classification Models/18. Logistic Regression Equation.mp4 3.6 MB
05. Univariate Profiling/2. Categorical Variables.mp4 3.6 MB
14. Model Diagnostics/1. Intro to Model Diagnostics.mp4 3.6 MB
15. Time-Series Forecasting/2. Seasonality.mp4 3.5 MB
02. Intro to the ML Landscape/4. The Machine Learning Landscape.mp4 3.5 MB
06. Multivariate Profiling/9. Numerical-Numerical.mp4 3.5 MB
04. Preliminary Data QA/5. Range Calculations.mp4 3.5 MB
21. Dimensionality Reduction/3. Principle Component Analysis.mp4 3.5 MB
06. Multivariate Profiling/6. Violin Plots.mp4 3.4 MB
05. Univariate Profiling/11. Univariate Data Profiling.mp4 3.4 MB
15. Time-Series Forecasting/11. Non-Linear Trends.mp4 3.4 MB
14. Model Diagnostics/9. Multicollinearity.mp4 3.3 MB
18. Clustering & Segmentation/10. KEY TAKEAWAYS Clustering & Segmentation.mp4 3.3 MB
09. Classification Models/5. Intro to Naïve Bayes.mp4 3.3 MB
19. Association Mining & Basket Analysis/2. Association Mining Basics.mp4 3.3 MB
06. Multivariate Profiling/16. Looking Ahead to Part 2.mp4 3.3 MB
20. Outlier Detection/1. Introduction.mp4 3.2 MB
06. Multivariate Profiling/14. BEST PRACTICES Multivariate Profiling.mp4 3.2 MB
17. Intro to Unsupervised ML/2. Common Unsupervised Techniques.mp4 3.2 MB
09. Classification Models/13. Random Forests.mp4 3.2 MB
04. Preliminary Data QA/2. Why QA.mp4 3.1 MB
13. Regression Modeling 101/4. Univariate Linear Regression.mp4 3.1 MB
19. Association Mining & Basket Analysis/5. Minimum Support Thresholds.mp4 3.1 MB
05. Univariate Profiling/15. Percentile.mp4 3.0 MB
17. Intro to Unsupervised ML/4. RECAP Feature Engineering.mp4 3.0 MB
04. Preliminary Data QA/10. BEST PRACTICES Preliminary QA.mp4 3.0 MB
18. Clustering & Segmentation/5. K-Means FAQs.mp4 3.0 MB
05. Univariate Profiling/18. Skewness.mp4 2.8 MB
06. Multivariate Profiling/7. Box Plots.mp4 2.8 MB
05. Univariate Profiling/17. Standard Deviation.mp4 2.8 MB
17. Intro to Unsupervised ML/5. KEY TAKEAWAYS Intro to Unsupervised ML.mp4 2.7 MB
21. Dimensionality Reduction/8. KEY TAKEAWAYS Dimensionality Reduction.mp4 2.7 MB
05. Univariate Profiling/14. Median.mp4 2.7 MB
09. Classification Models/1. Common Classification Models.mp4 2.6 MB
20. Outlier Detection/8. KEY TAKEAWAYS Outlier Detection.mp4 2.6 MB
14. Model Diagnostics/6. Null Hypothesis.mp4 2.5 MB
12. Intro to Regression/5. Prediction vs. Root-Cause Analysis.mp4 2.4 MB
14. Model Diagnostics/2. Sample Model Output.mp4 2.4 MB
09. Classification Models/2. Intro to K-Nearest Neighbors (KNN).mp4 2.3 MB
13. Regression Modeling 101/1. Intro to Regression Modeling.mp4 2.3 MB
21. Dimensionality Reduction/7. Advanced Techniques.mp4 2.2 MB
10. Model Selection & Tuning/9. Model Drift.mp4 2.1 MB
18. Clustering & Segmentation/1. Introduction.mp4 2.0 MB
10. Model Selection & Tuning/1. Intro to Selection & Tuning.mp4 1.9 MB
19. Association Mining & Basket Analysis/1. Introduction.mp4 1.8 MB
15. Time-Series Forecasting/16. Looking Ahead to Part 4.mp4 1.6 MB
22. Wrapping Up/1. Series Conclusion.mp4 1.4 MB
10. Model Selection & Tuning/11. Looking ahead to Part 3.mp4 1.3 MB
11. PART 3 Regression & Forecasting/1. Part 3 Regression & Forecasting.mp4 1.2 MB
16. PART 4 Unsupervised Learning/1. Part 4 Unsupervised Learning.mp4 1.0 MB
21. Dimensionality Reduction/1. Introduction.mp4 987.2 KB
22. Wrapping Up/2. 2023-09-26_17-36-30-fe18b28990bd3345572d56124cd324bb.png 117.0 KB
09. Classification Models/26.5 Classification Models.html 34.2 KB
05. Univariate Profiling/20.2 QUIZ Univariate Profiling.html 31.2 KB
18. Clustering & Segmentation/11.12 QUIZ Clustering & Segmentation.html 26.9 KB
04. Preliminary Data QA/11.1 QUIZ Preliminary Data QA.html 26.2 KB
19. Association Mining & Basket Analysis/12.13 QUIZ Association Mining.html 25.3 KB
06. Multivariate Profiling/15.3 QUIZ Multivariate Profiling.html 25.3 KB
08. Intro to Classification/9.4 Intro to Classification.html 24.6 KB
14. Model Diagnostics/12.9 QUIZ Model Diagnostics.html 24.1 KB
10. Model Selection & Tuning/10.6 Model Selection & Tuning.html 23.4 KB
12. Intro to Regression/6.7 QUIZ Intro to Regression.html 23.0 KB
13. Regression Modeling 101/9.8 QUIZ Regression Modeling.html 22.5 KB
15. Time-Series Forecasting/15.10 QUIZ Time-Series Forecasting.html 21.8 KB
20. Outlier Detection/9.14 QUIZ Outlier Detection.html 21.3 KB
21. Dimensionality Reduction/9.15 QUIZ Dimensionality Reduction.html 21.3 KB
17. Intro to Unsupervised ML/6.11 QUIZ Intro to Unsupervised ML.html 20.0 KB
04. Preliminary Data QA/9. CASE STUDY Preliminary QA.vtt 16.4 KB
18. Clustering & Segmentation/6. CASE STUDY K-Means.vtt 14.9 KB
22. Wrapping Up/2. BONUS LESSON.html 12.6 KB
09. Classification Models/4. CASE STUDY KNN.vtt 11.8 KB
13. Regression Modeling 101/8. CASE STUDY Non-Linear Regression.vtt 10.8 KB
13. Regression Modeling 101/5. CASE STUDY Univariate Linear Regression.vtt 10.8 KB
15. Time-Series Forecasting/8. CASE STUDY Seasonality with Linear Trend.vtt 10.6 KB
09. Classification Models/14. CASE STUDY Decision Trees.vtt 10.1 KB
15. Time-Series Forecasting/14. CASE STUDY Intervention Analysis.vtt 9.9 KB
09. Classification Models/21. CASE STUDY Logistic Regression.vtt 9.6 KB
15. Time-Series Forecasting/6. CASE STUDY Seasonality with One-Hot Encoding.vtt 9.5 KB
19. Association Mining & Basket Analysis/8. CASE STUDY Apriori.vtt 9.5 KB
09. Classification Models/8. CASE STUDY Naïve Bayes.vtt 9.4 KB
09. Classification Models/25. CASE STUDY Sentiment Analysis.vtt 8.0 KB
20. Outlier Detection/5. CASE STUDY Cross-Sectional Outlier.vtt 7.6 KB
14. Model Diagnostics/4. Mean Error Metrics (MSE, MAE, MAPE).vtt 7.5 KB
15. Time-Series Forecasting/12. CASE STUDY Non-Linear Trend.vtt 7.3 KB
13. Regression Modeling 101/6. Multiple Linear Regression.vtt 7.2 KB
05. Univariate Profiling/7. Histograms & Kernel Densities.vtt 6.9 KB
15. Time-Series Forecasting/10. CASE STUDY Smoothing.vtt 6.8 KB
09. Classification Models/7. Naïve Bayes Conditional Probability.vtt 6.6 KB
09. Classification Models/12. Decision Tree Examples.vtt 6.5 KB
06. Multivariate Profiling/13. CASE STUDY Correlation.vtt 6.4 KB
14. Model Diagnostics/3. R-Squared.vtt 6.4 KB
19. Association Mining & Basket Analysis/9. Markov Chains.vtt 6.2 KB
13. Regression Modeling 101/3. Least Squared Error.vtt 6.1 KB
06. Multivariate Profiling/3. CASE STUDY Heat Maps.vtt 6.0 KB
19. Association Mining & Basket Analysis/4. Basket Analysis Examples.vtt 5.9 KB
05. Univariate Profiling/8. CASE STUDY Histograms.vtt 5.7 KB
05. Univariate Profiling/10. CASE STUDY Normal Distribution.vtt 5.7 KB
09. Classification Models/3. KNN Examples.vtt 5.6 KB
19. Association Mining & Basket Analysis/10. CASE STUDY Markov Chains.vtt 5.6 KB
09. Classification Models/11. Entropy & Information Gain.vtt 5.6 KB
04. Preliminary Data QA/4. Empty Values.vtt 5.5 KB
09. Classification Models/24. Bag of Words Analysis.vtt 5.4 KB
10. Model Selection & Tuning/7. Multi-class Scoring.vtt 5.2 KB
08. Intro to Classification/4. Classification 101.vtt 5.1 KB
14. Model Diagnostics/11. RECAP Sample Model Output.vtt 5.0 KB
15. Time-Series Forecasting/4. CASE STUDY Seasonality with ACF.vtt 4.9 KB
01. Getting Started/2. READ ME Important Notes for New Students.html 4.8 KB
08. Intro to Classification/8. Overfitting.vtt 4.8 KB
13. Regression Modeling 101/2. Linear Relationships.vtt 4.7 KB
05. Univariate Profiling/5. Categorical Distributions.vtt 4.6 KB
08. Intro to Classification/3. RECAP Key Concepts.vtt 4.5 KB
08. Intro to Classification/6. Feature Engineering.vtt 4.5 KB
18. Clustering & Segmentation/3. Intro to K-Means.vtt 4.5 KB
09. Classification Models/19. The Likelihood Function.vtt 4.5 KB
06. Multivariate Profiling/1. Introduction.vtt 4.4 KB
13. Regression Modeling 101/7. Non-Linear Regression.vtt 4.4 KB
05. Univariate Profiling/9. Normal Distribution.vtt 4.3 KB
10. Model Selection & Tuning/3. Imbalanced Classes.vtt 4.3 KB
08. Intro to Classification/5. Classification Workflow.vtt 4.3 KB
10. Model Selection & Tuning/2. Hyperparameters.vtt 4.3 KB
14. Model Diagnostics/10. Variance Inflation Factor.vtt 4.2 KB
18. Clustering & Segmentation/7. Intro to Hierarchical Clustering.vtt 4.2 KB
05. Univariate Profiling/16. Variance.vtt 4.2 KB
19. Association Mining & Basket Analysis/6. Infrequent Itemsets.vtt 4.2 KB
06. Multivariate Profiling/10. Correlation.vtt 4.1 KB
06. Multivariate Profiling/2. Categorical-Categorical.vtt 4.1 KB
04. Preliminary Data QA/3. Variable Types.vtt 4.0 KB
14. Model Diagnostics/8. T-Values & P-Values.vtt 3.9 KB
05. Univariate Profiling/12. Mode.vtt 3.8 KB
20. Outlier Detection/4. Cross-Sectional Outlier Example.vtt 3.8 KB
04. Preliminary Data QA/1. Introduction.vtt 3.7 KB
06. Multivariate Profiling/5. Multivariate Kernel Densities.vtt 3.6 KB
09. Classification Models/17. False Positives vs. False Negatives.vtt 3.6 KB
01. Getting Started/4. Setting Expectations.vtt 3.6 KB
12. Intro to Regression/3. Regression 101.vtt 3.5 KB
12. Intro to Regression/4. Feature Engineering for Regression.vtt 3.5 KB
12. Intro to Regression/2. RECAP Key Concepts.vtt 3.4 KB
09. Classification Models/10. Decision Trees Entropy 101.vtt 3.4 KB
05. Univariate Profiling/4. Nominal vs. Ordinal.vtt 3.4 KB
02. Intro to the ML Landscape/3. The Machine Learning Process.vtt 3.4 KB
15. Time-Series Forecasting/13. Intervention Analysis.vtt 3.4 KB
15. Time-Series Forecasting/7. Linear Trending.vtt 3.3 KB
04. Preliminary Data QA/8. Table Structure.vtt 3.2 KB
05. Univariate Profiling/1. Introduction.vtt 3.2 KB
09. Classification Models/20. Multivariate Logistic Regression.vtt 3.1 KB
21. Dimensionality Reduction/6. Scree Plots.vtt 3.1 KB
09. Classification Models/16. Logistic Regression Example.vtt 3.1 KB
04. Preliminary Data QA/2. Why QA.vtt 3.1 KB
12. Intro to Regression/1. Supervised vs. Unsupervised Learning.vtt 3.1 KB
21. Dimensionality Reduction/5. Interpreting Components.vtt 3.1 KB
10. Model Selection & Tuning/5. Accuracy, Precision & Recall.vtt 3.1 KB
04. Preliminary Data QA/7. Left & Right Censored Data.vtt 3.1 KB
09. Classification Models/6. Naïve Bayes Frequency Tables.vtt 3.0 KB
20. Outlier Detection/7. Time-Series Outlier Example.vtt 3.0 KB
18. Clustering & Segmentation/4. WSS & Elbow Plots.vtt 3.0 KB
01. Getting Started/1. Course Structure & Outline.vtt 2.9 KB
03. PART 1 QA & Data Profiling/1. Part 1 QA & Data Profiling.vtt 2.9 KB
21. Dimensionality Reduction/2. Dimensionality Reduction Basics.vtt 2.9 KB
21. Dimensionality Reduction/4. PCA Example.vtt 2.9 KB
08. Intro to Classification/2. Classification vs. Regression.vtt 2.8 KB
10. Model Selection & Tuning/4. Confusion Matrix.vtt 2.8 KB
10. Model Selection & Tuning/6. Multi-class Confusion Matrix.vtt 2.8 KB
06. Multivariate Profiling/12. Visualizing Third Dimension.vtt 2.8 KB
15. Time-Series Forecasting/1. Intro to Forecasting.vtt 2.8 KB
07. PART 2 Classification Modeling/1. Part 2 Classification Modeling.vtt 2.8 KB
06. Multivariate Profiling/8. Limitations of Categorical Distributions.vtt 2.8 KB
15. Time-Series Forecasting/3. Auto Correlation Function.vtt 2.7 KB
02. Intro to the ML Landscape/4. The Machine Learning Landscape.vtt 2.7 KB
06. Multivariate Profiling/4. Categorical-Numerical.vtt 2.6 KB
06. Multivariate Profiling/11. Correlation vs. Causation.vtt 2.6 KB
17. Intro to Unsupervised ML/1. Supervised vs. Unsupervised Learning.vtt 2.6 KB
14. Model Diagnostics/5. Homoskedasticity.vtt 2.6 KB
15. Time-Series Forecasting/5. One-Hot Encoding.vtt 2.6 KB
20. Outlier Detection/2. Outlier Detection Basics.vtt 2.6 KB
18. Clustering & Segmentation/8. Anatomy of a Dendrogram.vtt 2.6 KB
20. Outlier Detection/3. Cross-Sectional Outliers.vtt 2.6 KB
08. Intro to Classification/1. Supervised vs. Unsupervised Learning.vtt 2.5 KB
04. Preliminary Data QA/5. Range Calculations.vtt 2.5 KB
05. Univariate Profiling/19. BEST PRACTICES Univariate Profiling.vtt 2.5 KB
18. Clustering & Segmentation/2. Clustering Basics.vtt 2.5 KB
04. Preliminary Data QA/6. Count Calculations.vtt 2.5 KB
09. Classification Models/22. Intro to Sentiment Analysis.vtt 2.5 KB
05. Univariate Profiling/11. Univariate Data Profiling.vtt 2.4 KB
18. Clustering & Segmentation/9. Hierarchical Clustering FAQs.vtt 2.4 KB
09. Classification Models/18. Logistic Regression Equation.vtt 2.4 KB
05. Univariate Profiling/13. Mean.vtt 2.4 KB
14. Model Diagnostics/7. F-Significance.vtt 2.4 KB
05. Univariate Profiling/6. Numerical Variables.vtt 2.4 KB
14. Model Diagnostics/1. Intro to Model Diagnostics.vtt 2.4 KB
09. Classification Models/15. Intro to Logistic Regression.vtt 2.3 KB
09. Classification Models/9. Intro to Decision Trees.vtt 2.3 KB
15. Time-Series Forecasting/9. Smoothing.vtt 2.3 KB
09. Classification Models/23. Cleaning Text Data.vtt 2.3 KB
17. Intro to Unsupervised ML/3. Unsupervised ML Workflow.vtt 2.3 KB
15. Time-Series Forecasting/2. Seasonality.vtt 2.2 KB
19. Association Mining & Basket Analysis/7. Multiple Item Sets.vtt 2.2 KB
06. Multivariate Profiling/9. Numerical-Numerical.vtt 2.2 KB
10. Model Selection & Tuning/8. Model Selection.vtt 2.2 KB
20. Outlier Detection/6. Time-Series Outliers.vtt 2.2 KB
05. Univariate Profiling/3. Discretization.vtt 2.2 KB
06. Multivariate Profiling/6. Violin Plots.vtt 2.1 KB
05. Univariate Profiling/18. Skewness.vtt 2.1 KB
09. Classification Models/5. Intro to Naïve Bayes.vtt 2.1 KB
14. Model Diagnostics/9. Multicollinearity.vtt 2.1 KB
05. Univariate Profiling/2. Categorical Variables.vtt 2.1 KB
08. Intro to Classification/7. Data Splitting.vtt 2.1 KB
19. Association Mining & Basket Analysis/3. The Apriori Algorithm.vtt 1.9 KB
15. Time-Series Forecasting/11. Non-Linear Trends.vtt 1.9 KB
04. Preliminary Data QA/10. BEST PRACTICES Preliminary QA.vtt 1.9 KB
17. Intro to Unsupervised ML/2. Common Unsupervised Techniques.vtt 1.9 KB
18. Clustering & Segmentation/10. KEY TAKEAWAYS Clustering & Segmentation.vtt 1.9 KB
05. Univariate Profiling/15. Percentile.vtt 1.9 KB
19. Association Mining & Basket Analysis/11. KEY TAKEAWAYS Association Mining.vtt 1.9 KB
13. Regression Modeling 101/4. Univariate Linear Regression.vtt 1.8 KB
19. Association Mining & Basket Analysis/2. Association Mining Basics.vtt 1.8 KB
21. Dimensionality Reduction/3. Principle Component Analysis.vtt 1.8 KB
06. Multivariate Profiling/14. BEST PRACTICES Multivariate Profiling.vtt 1.8 KB
17. Intro to Unsupervised ML/5. KEY TAKEAWAYS Intro to Unsupervised ML.vtt 1.8 KB
17. Intro to Unsupervised ML/4. RECAP Feature Engineering.vtt 1.8 KB
05. Univariate Profiling/17. Standard Deviation.vtt 1.7 KB
20. Outlier Detection/1. Introduction.vtt 1.7 KB
06. Multivariate Profiling/7. Box Plots.vtt 1.7 KB
18. Clustering & Segmentation/5. K-Means FAQs.vtt 1.6 KB
05. Univariate Profiling/14. Median.vtt 1.6 KB
12. Intro to Regression/5. Prediction vs. Root-Cause Analysis.vtt 1.6 KB
09. Classification Models/1. Common Classification Models.vtt 1.6 KB
14. Model Diagnostics/6. Null Hypothesis.vtt 1.5 KB
09. Classification Models/2. Intro to K-Nearest Neighbors (KNN).vtt 1.5 KB
02. Intro to the ML Landscape/2. When is ML the right fit.vtt 1.5 KB
09. Classification Models/13. Random Forests.vtt 1.5 KB
10. Model Selection & Tuning/9. Model Drift.vtt 1.5 KB
19. Association Mining & Basket Analysis/5. Minimum Support Thresholds.vtt 1.5 KB
13. Regression Modeling 101/1. Intro to Regression Modeling.vtt 1.5 KB
06. Multivariate Profiling/16. Looking Ahead to Part 2.vtt 1.4 KB
21. Dimensionality Reduction/8. KEY TAKEAWAYS Dimensionality Reduction.vtt 1.4 KB
18. Clustering & Segmentation/1. Introduction.vtt 1.3 KB
20. Outlier Detection/8. KEY TAKEAWAYS Outlier Detection.vtt 1.3 KB
02. Intro to the ML Landscape/1. Intro to Machine Learning.vtt 1.3 KB
21. Dimensionality Reduction/7. Advanced Techniques.vtt 1.3 KB
10. Model Selection & Tuning/1. Intro to Selection & Tuning.vtt 1.2 KB
15. Time-Series Forecasting/16. Looking Ahead to Part 4.vtt 1.1 KB
19. Association Mining & Basket Analysis/1. Introduction.vtt 1.0 KB
14. Model Diagnostics/2. Sample Model Output.vtt 1.0 KB
22. Wrapping Up/1. Series Conclusion.vtt 869 bytes
10. Model Selection & Tuning/11. Looking ahead to Part 3.vtt 735 bytes
11. PART 3 Regression & Forecasting/1. Part 3 Regression & Forecasting.vtt 636 bytes
21. Dimensionality Reduction/1. Introduction.vtt 609 bytes
01. Getting Started/3. DOWNLOAD Course Resources.html 578 bytes
16. PART 4 Unsupervised Learning/1. Part 4 Unsupervised Learning.vtt 396 bytes

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