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DP-100 Part 3 - Deployment and Working with SDK

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3:10:08

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  • 001 Course Introduction.mp4
    01:01
  • 001 Study Guide PDF.pdf
  • 002 About the Training Architect.mp4
    01:11
  • 003 About the Exam.mp4
    06:34
  • 004 A Note on Data Science and Mathematics.mp4
    01:36
  • 005 A Note on Python.mp4
    02:08
  • 005 Quick Note PANDAS refers to Python Data Analysis Library.txt
  • 006 Azure Machine Learning SDK.mp4
    04:22
  • 007 DP100 Part 1 Course.txt
  • 007 DP100 Part 2 Course.txt
  • 007 Introduction to Python Scripting Course.txt
  • 007 Path to Certification.mp4
    02:41
  • 007 Using Pythons Math Science and Engineering Libraries Course.txt
  • 001 Workspace and Compute Preparation.mp4
    08:56
  • 002 Configuring Run Settings for a Script.mp4
    07:16
  • 003 Consuming Data from a Dataset in an Experiment by Using SDK.mp4
    05:07
  • 004 Configure Run Settings for a Script.txt
  • 004 Section Review.mp4
    03:34
  • 004 Working with Datasets Using SDK.txt
  • 004 Workspace and Compute Preparation.txt
  • 001 Creating a Pipeline by Using the SDK Part 1.mp4
    06:05
  • 002 Creating a Pipeline by Using the SDK Part 2.mp4
    03:42
  • 001 Using Automated ML Interface in Azure Machine Learning Studio.mp4
    07:58
  • 002 Preprocessing Options.mp4
    06:08
  • 003 Creating a Pipeline Using SDK.txt
  • 003 Preprocessing.txt
  • 003 Section Review.mp4
    02:45
  • 003 Using Automated ML Interface.txt
  • 001 What Is a Hyperdrive and Can I Use It to Get to the Future.mp4
    05:41
  • 002 Tuning Hyperparameters for Peak Performance.mp4
    05:18
  • 003 Selecting a Sampling Method.mp4
    04:30
  • 004 Smokey and the Bandit and All His Rowdy Friends.mp4
    03:44
  • 005 Finding the Model That Has Optimal Hyperparameter Values.mp4
    05:45
  • 001 Model Interpretability and Explainers in Azure.mp4
    07:05
  • 002 Model Interpretability in Python.mp4
    07:09
  • 003 Hyperparameter Tuning.txt
  • 003 Model Interpretability.txt
  • 003 Section Review.mp4
    03:26
  • 001 Registering a Trained Model.mp4
    03:54
  • 002 Monitoring Model Usage with Azure Monitor.mp4
    03:53
  • 003 Monitoring Data Drift.mp4
    10:03
  • 001 Evaluating Deployment Options.mp4
    08:05
  • 002 Considering Security for Deployed Services.mp4
    02:17
  • 003 Microsoft Troubleshooting Guide.txt
  • 003 Troubleshooting Container Issues.mp4
    04:55
  • 004 Considering Security.txt
  • 004 Evaluating Deployment Options.txt
  • 004 Monitoring Models.txt
  • 004 Registering a Trained Model.txt
  • 004 Section Review.mp4
    03:10
  • 004 Troubleshooting Container Issues.txt
  • 001 Publishing a Batch Inferencing Pipeline.mp4
    05:00
  • 001 Azure Machine Learning Workspace Creation.mp4
    04:50
  • 002 Azure Machine Learning Data Management.mp4
    03:15
  • 003 Azure Machine Learning Compute.mp4
    05:17
  • 001 Azure Machine Learning Algorithm Cheat Sheet.txt
  • 001 How to Select Algorithms for Azure Machine Learning.txt
  • 001 Machine Learning Algorithms You Need to Know.mp4
    06:05
  • 002 Feature Selection Modules.txt
  • 002 Feature Selection Some Tools and Concepts You Need to Know.mp4
    03:48
  • 002 Filter-Based Feature Selection.txt
  • 003 Classic Machine Learning Models.mp4
    05:20
  • 001 Thanks and Whats Next.mp4
    01:13
  • 002 Exam Tips.mp4
    05:21
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    A Cloud Guru is an online training platform for people interested in Information Technology. Most of the courses offered prepare students to take certification exams for the three major cloud providers.
    • language english
    • Training sessions 40
    • duration 3:10:08
    • Release Date 2023/12/08