Linux Academy DP 100 Part 2 Modeling-APoLLo | Apps-Tutorials | MP4 | 3.60 GiB
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RELEASE: Linux.Academy.DP.100.Part.2.Modeling-APoLLo
URL: https://linuxacademy.com
SOURCE: Linux Academy
DATE: 2020-07-18
ex.FiLES Yes
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SAUCE00 Smooth 202004154] P Y IBM VGA
114M 1.Introduction 30M 1.Introduction/535-6238-1 - Course Introduction.mp4 13M 1.Introduction/535-6238-2 - About the Training Architect.mp4 20M 1.Introduction/535-6238-3 - Using the DP-100 Essentials Guide.mp4 25M 1.Introduction/535-6238-4 - About the Exam.mp4 29M 1.Introduction/535-6238-5 - A Note on Data Science and Mathematics.mp4 249M 2.Azure.Machine.Learning.Pipelines 56M 2.Azure.Machine.Learning.Pipelines/535-6239-1 - A Refresh on Azure Machine Learning Pipelines.mp4 100M 2.Azure.Machine.Learning.Pipelines/535-6239-2 - Designer Modules to Define Pipeline Data Flow.mp4 33M 2.Azure.Machine.Learning.Pipelines/535-6239-3 - Using Custom Code Modules in Designer.mp4 61M 2.Azure.Machine.Learning.Pipelines/535-6239-4 - Exam Essentials and References.mp4 1.2G 3.Machine.Learning.Algorithm 106M 3.Machine.Learning.Algorithm/535-6241-1 - An Introduction to Terminology.mp4 56M 3.Machine.Learning.Algorithm/535-6241-10 - Exam Essentials and References.mp4 83M 3.Machine.Learning.Algorithm/535-6241-2 - How to Select Algorithms in Azure Machine Learning.mp4 157M 3.Machine.Learning.Algorithm/535-6241-3 - Text Analytics.mp4 166M 3.Machine.Learning.Algorithm/535-6241-4 - Regression.mp4 215M 3.Machine.Learning.Algorithm/535-6241-5 - Multiclass Classification.mp4 121M 3.Machine.Learning.Algorithm/535-6241-6 - Image Classification.mp4 91M 3.Machine.Learning.Algorithm/535-6241-7 - Anomaly Detection.mp4 89M 3.Machine.Learning.Algorithm/535-6241-8 - Clustering.mp4 61M 3.Machine.Learning.Algorithm/535-6241-9 - Recommenders.mp4 701M 4.Feature.Selection 102M 4.Feature.Selection/535-6242-1 - An Introduction to Feature Selection.mp4 122M 4.Feature.Selection/535-6242-10 - Exam Essentials and References.mp4 96M 4.Feature.Selection/535-6242-2 - Intro to Feature Extraction.mp4 40M 4.Feature.Selection/535-6242-3 - Pearson's Correlation.mp4 79M 4.Feature.Selection/535-6242-4 - Mutual Information Score.mp4 65M 4.Feature.Selection/535-6242-5 - Kendall's Correlation Coefficient.mp4 76M 4.Feature.Selection/535-6242-6 - Spearman's Correlation Coefficient.mp4 40M 4.Feature.Selection/535-6242-7 - Chi-Squared Statistic.mp4 46M 4.Feature.Selection/535-6242-8 - Fisher Score.mp4 39M 4.Feature.Selection/535-6242-9 - Count-Based Feature Selection.mp4 302M 5.Classic.Machine.Learning.Models 63M 5.Classic.Machine.Learning.Models/535-6243-1 - Introduction to Neural Networks.mp4 35M 5.Classic.Machine.Learning.Models/535-6243-2 - RNN.mp4 41M 5.Classic.Machine.Learning.Models/535-6243-3 - DNN.mp4 38M 5.Classic.Machine.Learning.Models/535-6243-4 - CNN.mp4 95M 5.Classic.Machine.Learning.Models/535-6243-5 - SMOTE.mp4 32M 5.Classic.Machine.Learning.Models/535-6243-6 - Exam Essentials and References.mp4 257M 6.Run.Training.Scripts.in.an.Azure.Machine.Learning.Workspace 49M 6.Run.Training.Scripts.in.an.Azure.Machine.Learning.Workspace/535-6244-1 - Azure Machine Learning SDK Introduction.mp4 31M 6.Run.Training.Scripts.in.an.Azure.Machine.Learning.Workspace/535-6244-2 - Create an Experiment with SDK.mp4 47M 6.Run.Training.Scripts.in.an.Azure.Machine.Learning.Workspace/535-6244-3 - Consume Data from a Datastore with SDK.mp4 61M 6.Run.Training.Scripts.in.an.Azure.Machine.Learning.Workspace/535-6244-4 - Consume Data from a Data Set with SDK.mp4 47M 6.Run.Training.Scripts.in.an.Azure.Machine.Learning.Workspace/535-6244-5 - Choosing an Estimator in Azure Machine Learning.mp4 23M 6.Run.Training.Scripts.in.an.Azure.Machine.Learning.Workspace/535-6244-6 - Exam Essentials and References.mp4 800M 7.Generate.Metrics.from.an.Experiment.Run 264M 7.Generate.Metrics.from.an.Experiment.Run/6245-1 - Logging Metrics from an Experiment Run.mp4 215M 7.Generate.Metrics.from.an.Experiment.Run/6245-2 - Retrieving and Viewing Experiment Outputs.mp4 297M 7.Generate.Metrics.from.an.Experiment.Run/6245-3 - Using Logs to Troubleshoot Experiment Run Errors.mp4 27M 7.Generate.Metrics.from.an.Experiment.Run/6245-4 - Exam Essentials and References.mp4 53M 8.Conclusion 33M 8.Conclusion/535-6246-1 - Review and Final Notes.mp4 21M 8.Conclusion/535-6246-2 - What's Next.mp4 75M ex.FiLES.zip 3.6G total
File: 535-6238-1 - Course Introduction.mp4 Size: 30593061 bytes (29.18 MiB), duration: 00:03:08, avg.bitrate: 1302 kb/s Audio: aac, 44100 Hz, stereo (und) Video: h264, yuv420p, 1920x1080, 30.00 fps(r) (und)
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Keywords: Linux, Academy, 100, Part, Modeling, APoLLo
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