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| Archived
files |
|
1.Introduction\535-6238-1 - Course Introduction.mp4
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|
30,593,061 |
A3BFB792 |
|
1.Introduction\535-6238-2 - About the Training Architect.mp4
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|
13,344,103 |
3266106A |
|
1.Introduction\535-6238-3 - Using the DP-100 Essentials Guide.mp4
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|
20,435,066 |
A8A780C8 |
|
1.Introduction\535-6238-4 - About the Exam.mp4
[c64ed3ad49fa0be2]
|
25,333,728 |
A9008480 |
|
1.Introduction\535-6238-5 - A Note on Data Science and Mathematics.mp4
[b6ab1099910a8dbc]
|
29,448,948 |
10B54147 |
|
2.Azure.Machine.Learning.Pipelines\535-6239-1 - A Refresh on Azure Machine Learning Pipelines.mp4
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|
57,700,087 |
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2.Azure.Machine.Learning.Pipelines\535-6239-2 - Designer Modules to Define Pipeline Data Flow.mp4
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|
104,571,535 |
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2.Azure.Machine.Learning.Pipelines\535-6239-3 - Using Custom Code Modules in Designer.mp4
[fea17500742fa4a4]
|
34,471,832 |
9035AB8D |
|
2.Azure.Machine.Learning.Pipelines\535-6239-4 - Exam Essentials and References.mp4
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|
63,488,880 |
E059F892 |
|
3.Machine.Learning.Algorithm\535-6241-1 - An Introduction to Terminology.mp4
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|
110,190,092 |
A1D11E66 |
|
3.Machine.Learning.Algorithm\535-6241-10 - Exam Essentials and References.mp4
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|
57,784,470 |
A1AB4423 |
|
3.Machine.Learning.Algorithm\535-6241-2 - How to Select Algorithms in Azure Machine Learning.mp4
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|
86,079,915 |
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3.Machine.Learning.Algorithm\535-6241-3 - Text Analytics.mp4
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3.Machine.Learning.Algorithm\535-6241-4 - Regression.mp4
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3.Machine.Learning.Algorithm\535-6241-5 - Multiclass Classification.mp4
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3.Machine.Learning.Algorithm\535-6241-6 - Image Classification.mp4
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3.Machine.Learning.Algorithm\535-6241-7 - Anomaly Detection.mp4
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3.Machine.Learning.Algorithm\535-6241-8 - Clustering.mp4
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3.Machine.Learning.Algorithm\535-6241-9 - Recommenders.mp4
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4.Feature.Selection\535-6242-1 - An Introduction to Feature Selection.mp4
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|
106,828,454 |
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|
4.Feature.Selection\535-6242-10 - Exam Essentials and References.mp4
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|
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4.Feature.Selection\535-6242-2 - Intro to Feature Extraction.mp4
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4.Feature.Selection\535-6242-3 - Pearson's Correlation.mp4
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4.Feature.Selection\535-6242-4 - Mutual Information Score.mp4
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4.Feature.Selection\535-6242-5 - Kendall's Correlation Coefficient.mp4
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4.Feature.Selection\535-6242-6 - Spearman's Correlation Coefficient.mp4
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4.Feature.Selection\535-6242-7 - Chi-Squared Statistic.mp4
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4.Feature.Selection\535-6242-8 - Fisher Score.mp4
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48,134,286 |
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4.Feature.Selection\535-6242-9 - Count-Based Feature Selection.mp4
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|
40,593,061 |
2E34BB76 |
|
5.Classic.Machine.Learning.Models\535-6243-1 - Introduction to Neural Networks.mp4
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|
65,440,537 |
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|
5.Classic.Machine.Learning.Models\535-6243-2 - RNN.mp4
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5.Classic.Machine.Learning.Models\535-6243-3 - DNN.mp4
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5.Classic.Machine.Learning.Models\535-6243-4 - CNN.mp4
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5.Classic.Machine.Learning.Models\535-6243-5 - SMOTE.mp4
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5.Classic.Machine.Learning.Models\535-6243-6 - Exam Essentials and References.mp4
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32,704,936 |
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6.Run.Training.Scripts.in.an.Azure.Machine.Learning.Workspace\535-6244-1 - Azure Machine Learning SDK Introduction.mp4
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51,378,421 |
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6.Run.Training.Scripts.in.an.Azure.Machine.Learning.Workspace\535-6244-2 - Create an Experiment with SDK.mp4
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6.Run.Training.Scripts.in.an.Azure.Machine.Learning.Workspace\535-6244-3 - Consume Data from a Datastore with SDK.mp4
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6.Run.Training.Scripts.in.an.Azure.Machine.Learning.Workspace\535-6244-4 - Consume Data from a Data Set with SDK.mp4
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6.Run.Training.Scripts.in.an.Azure.Machine.Learning.Workspace\535-6244-5 - Choosing an Estimator in Azure Machine Learning.mp4
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49,021,256 |
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6.Run.Training.Scripts.in.an.Azure.Machine.Learning.Workspace\535-6244-6 - Exam Essentials and References.mp4
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7.Generate.Metrics.from.an.Experiment.Run\6245-1 - Logging Metrics from an Experiment Run.mp4
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275,801,111 |
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7.Generate.Metrics.from.an.Experiment.Run\6245-2 - Retrieving and Viewing Experiment Outputs.mp4
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7.Generate.Metrics.from.an.Experiment.Run\6245-3 - Using Logs to Troubleshoot Experiment Run Errors.mp4
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7.Generate.Metrics.from.an.Experiment.Run\6245-4 - Exam Essentials and References.mp4
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8.Conclusion\535-6246-1 - Review and Final Notes.mp4
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8.Conclusion\535-6246-2 - What's Next.mp4
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ex.FiLES.zip |
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