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Microsoft Azure: Machine Learning

Cloud has become the go-to place today for storage, computation, security, analytics and many other services. The cloud is disrupting the analytics industry and taking over processes and applications by storm! This course helps you understand how the cloud makes analytics and machine learning easier.

What You’ll Learn

In this workshop, participants will build a machine learning pipeline using various MicrosoftAzure tools and services. The workshop will take participant through how to plan data loads and imports, followed by data preparation, such as cleaning and manipulating the data for testing, training various Machine Learning models and deploying them into a production environment.

Please click the event link in the timetable for the respective price.

Course Plan

MODULE 1: DATA SCIENCE LIFECYCLE AND MACHINE LEARNING INTRODUCTION

This module will take participants through the foundations of the data science lifecycle, the different steps involved, and the common machine learning techniques employed across various industry sectors today.

MODULE 2: MACHINE LEARNING USING AZURE MACHINE LEARNING (AML) STUDIO
  • AML Studio Components
  • Data Import
  • Data Cleaning and Manipulation
  • Machine Learning Experimentation
  • Deploying Machine Learning Models
  • Consuming APIs in Excel
MODULE 3: MACHINE LEARNING USING AZURE MACHINE LEARNING SERVICES
  • Introduction to Azure Machine Learning Services
  • Building Model Pipelines using Azure Machine Learning Services
  • Operationalizing Models

Timetable

Please check back for available dates or subscribe to stay updated!

Prerequisites

Having an overview of Microsoft Azure would be helpful for this course.

About the Course

Here are a few of the the takeaways that participants will gain:

  • Participants will be taught basic machine learning processes and how different components and tasks of Azure Machine Learning map to each step of the process.
  • Understand how to import and manipulate data with Azure Machine Learning Studio.
  • How to evaluate model performance in Azure Machine Learning Studio.
  • How to leverage external scripts written in R or Python with Azure Machine Learning Studio.
  • How to operationalize an Azure Machine Learning Studio model for consumption by an application.
  • Introduction to Azure Machine Learning Services

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