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Lynda - Machine Learning and AI Foundations - Clustering and Association

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Title: Lynda - Machine Learning and AI FoundationsGroup: NOGRPSource: Lynda
Info Hash
D308C7575A0F8D455153651FF6385F3A384DB8E0
Source
Unverified
Total Size
532.04 MB
Total Files
85
Seeders
1
Leechers
0
Health
1.00
Score
2
Type
Bookware

File List

FileSize
Exercise Files/Ex_Files_Machine_Learning_AI_Clustering.zip24.98 MB
1.Introduction/01.Welcome.mp46.05 MB
1.Introduction/02.What you should know.en.srt3.87 KB
1.Introduction/02.What you should know.mp43.28 MB
1.Introduction/03.Using the exercise files.en.srt2.18 KB
1.Introduction/03.Using the exercise files.mp43.99 MB
1.Introduction/04.What is unsupervised machine learning.en.srt9.49 KB
1.Introduction/04.What is unsupervised machine learning.mp49.31 MB
2.1. What Is Cluster Analysis/05.Looking at the data with a 2D scatter plot.en.srt9.38 KB
2.1. What Is Cluster Analysis/05.Looking at the data with a 2D scatter plot.mp418.68 MB
2.1. What Is Cluster Analysis/06.Understanding hierarchical cluster analysis.en.srt8.37 KB
2.1. What Is Cluster Analysis/06.Understanding hierarchical cluster analysis.mp418.51 MB
2.1. What Is Cluster Analysis/07.Running hierarchical cluster analysis.en.srt6.54 KB
2.1. What Is Cluster Analysis/07.Running hierarchical cluster analysis.mp410.68 MB
2.1. What Is Cluster Analysis/08.Interpreting a dendrogram.en.srt6.08 KB
2.1. What Is Cluster Analysis/08.Interpreting a dendrogram.mp410.42 MB
2.1. What Is Cluster Analysis/09.Methods for measuring distance.en.srt9.31 KB
2.1. What Is Cluster Analysis/09.Methods for measuring distance.mp415.95 MB
2.1. What Is Cluster Analysis/10.What is k-nearest neighbors.en.srt8.48 KB
2.1. What Is Cluster Analysis/10.What is k-nearest neighbors.mp412.14 MB
3.2. K-Means/11.How does k-means work.en.srt3.18 KB
3.2. K-Means/11.How does k-means work.mp46.15 MB
3.2. K-Means/12.Which variables should be used with k-means.en.srt5.1 KB
3.2. K-Means/12.Which variables should be used with k-means.mp48.56 MB
3.2. K-Means/13.Interpreting a box plot.en.srt11.07 KB
3.2. K-Means/13.Interpreting a box plot.mp48.63 MB
3.2. K-Means/14.Running a k-means cluster analysis.en.srt5.32 KB
3.2. K-Means/14.Running a k-means cluster analysis.mp410.37 MB
3.2. K-Means/15.Interpreting cluster analysis output.en.srt9.4 KB
3.2. K-Means/15.Interpreting cluster analysis output.mp414.38 MB
3.2. K-Means/16.What does silhouette mean.en.srt3.62 KB
3.2. K-Means/16.What does silhouette mean.mp43.22 MB
3.2. K-Means/17.Which cases should be used with k-means.en.srt7.63 KB
3.2. K-Means/17.Which cases should be used with k-means.mp411.14 MB
3.2. K-Means/18.Finding optimum value for k - k = 3.en.srt8.19 KB
3.2. K-Means/18.Finding optimum value for k - k = 3.mp412.57 MB
3.2. K-Means/19.Finding optimum value for k - k = 4.en.srt9.57 KB
3.2. K-Means/19.Finding optimum value for k - k = 4.mp414.18 MB
3.2. K-Means/20.Finding optimum value for k - k = 5.en.srt7.78 KB
3.2. K-Means/20.Finding optimum value for k - k = 5.mp412.17 MB
3.2. K-Means/21.What the best solution.en.srt5.55 KB
3.2. K-Means/21.What the best solution.mp49.91 MB
4.3. Visualizing and Reporting Cluster Solutions/22.Summarizing cluster means in a table.en.srt8.17 KB
4.3. Visualizing and Reporting Cluster Solutions/22.Summarizing cluster means in a table.mp414.24 MB
4.3. Visualizing and Reporting Cluster Solutions/23.Traffic Light feature in Excel.en.srt5.62 KB
4.3. Visualizing and Reporting Cluster Solutions/23.Traffic Light feature in Excel.mp49.21 MB
4.3. Visualizing and Reporting Cluster Solutions/24.Line graphs.en.srt11.91 KB
4.3. Visualizing and Reporting Cluster Solutions/24.Line graphs.mp419.45 MB
5.4. Cluster Methods for Categorical Variables/25.Relating clusters to categories statistically.en.srt10.78 KB
5.4. Cluster Methods for Categorical Variables/25.Relating clusters to categories statistically.mp417.71 MB
5.4. Cluster Methods for Categorical Variables/26.Relating clusters to categories visually.en.srt4.91 KB
5.4. Cluster Methods for Categorical Variables/26.Relating clusters to categories visually.mp46.59 MB
5.4. Cluster Methods for Categorical Variables/27.Running a multiple correspondence analysis.en.srt8.53 KB
5.4. Cluster Methods for Categorical Variables/27.Running a multiple correspondence analysis.mp416.99 MB
5.4. Cluster Methods for Categorical Variables/28.Interpreting a perceptual map.en.srt5.09 KB
5.4. Cluster Methods for Categorical Variables/28.Interpreting a perceptual map.mp411.07 MB
5.4. Cluster Methods for Categorical Variables/29.Using cluster analysis and decision trees together.en.srt14.85 KB
5.4. Cluster Methods for Categorical Variables/29.Using cluster analysis and decision trees together.mp414.2 MB
5.4. Cluster Methods for Categorical Variables/30.A BIRCH_two-step example.en.srt7.54 KB
5.4. Cluster Methods for Categorical Variables/30.A BIRCH_two-step example.mp413.09 MB
5.4. Cluster Methods for Categorical Variables/31.A self organizing map example.en.srt11.05 KB
5.4. Cluster Methods for Categorical Variables/31.A self organizing map example.mp420.3 MB
6.5. Anomaly Detection/32.The k = 1 trick.en.srt11.08 KB
6.5. Anomaly Detection/32.The k = 1 trick.mp420.7 MB
6.5. Anomaly Detection/33.Anomaly detection algorithms.en.srt6.87 KB
6.5. Anomaly Detection/33.Anomaly detection algorithms.mp414.45 MB
6.5. Anomaly Detection/34.Using SOM for anomaly detection.en.srt9.88 KB
6.5. Anomaly Detection/34.Using SOM for anomaly detection.mp421.72 MB
7.6. Association Rules and Sequence Detection/35.Intro to association rules and sequence analysis.en.srt7.86 KB
7.6. Association Rules and Sequence Detection/35.Intro to association rules and sequence analysis.mp47.22 MB
7.6. Association Rules and Sequence Detection/36.Running association rules.en.srt9.33 KB
7.6. Association Rules and Sequence Detection/36.Running association rules.mp418.57 MB
7.6. Association Rules and Sequence Detection/37.Some association rules terminology.en.srt5.14 KB
7.6. Association Rules and Sequence Detection/37.Some association rules terminology.mp44.48 MB
7.6. Association Rules and Sequence Detection/38.Interpreting association rules.en.srt11.25 KB
7.6. Association Rules and Sequence Detection/38.Interpreting association rules.mp418.15 MB
7.6. Association Rules and Sequence Detection/39.Putting association rules to use.en.srt7.77 KB
7.6. Association Rules and Sequence Detection/39.Putting association rules to use.mp415.63 MB
7.6. Association Rules and Sequence Detection/40.Comparing clustering and association rules.en.srt4.51 KB
7.6. Association Rules and Sequence Detection/40.Comparing clustering and association rules.mp45.81 MB
7.6. Association Rules and Sequence Detection/41.Sequence detection.en.srt8.84 KB
7.6. Association Rules and Sequence Detection/41.Sequence detection.mp414.44 MB
8.Conclusion/42.Next steps.en.srt2.72 KB
8.Conclusion/42.Next steps.mp42.42 MB
1.Introduction/01.Welcome.en.srt1.32 KB

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