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Designing and Implementing a Data Science Solution on Azure Path (DP-100) with Practice Exam
00a Course Overview
Course Overview (3:09)
01 What Is Microsoft Azure Machine Learning (3:24)
02 What Is Microsoft Certified Azure Data Scientist Associate (5:10)
Source Files
02 Introduction to Cloud Computing for Machine Learning
01 Why Use The Cloud For Machine Learning (2:38)
02 Benefits of Cloud Computing (1:17)
03 Public Vs Private Cloud Computing (3:18)
04 Managed Vs Unmanaged Cloud Computing (1:30)
05 IaaS Vs PaaS Vs SaaS In Cloud Computing (3:33)
06 Google Cloud vs AWS vs Azure For Machine Learning (3:32)
Source Files
03 Introduction to Azure Machine Learning
What Is Azure Machine Learning Studio (2:17)
Source Files
04 Build a cluster and pipeline in Azure Machine Learning
01 Build An Azure Machine Learning Workspace (12:51)
02 Build A New Compute Cluster In Microsoft Azure Ml (6:08)
03A What Is Azure Machine Learning Designer (3:16)
03 Build A Pipeline In Microsoft Azure Ml Designer (4:25)
Source Files
05 Build a dataset in Microsoft Azure ML Studio
01 Build A Dataset In Microsoft Azure Ml Designer (3:48)
02 Clean Missing Data In Microsoft Azure Ml Designer (10:26)
03 Normalize Data In Microsoft Azure Ml Studio (4:24)
04 Run A Data Transformation Pipeline In Microsoft Azure Ml Designer (2:09)
Source Files
06 Build a regression machine learning model with Azure Machine Learning
00 What Is Linear Regression (5:03)
01 Build A Model Training Pipeline In Microsoft Azure Ml Studio (5:03)
02 Evaluate A Machine Learning Model In Microsoft Azure Ml (7:08)
Source Files
Test Your Knowledge
Practice Exam
05 IaaS Vs PaaS Vs SaaS In Cloud Computing
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