Creating & Deploying Microsoft Azure Machine Learning Studio Solutions

via

Pluralsight

Course Features

Duration

2.93 hours

Delivery Method

Online

Available on

Downloadable Courses

Accessibility

Mobile, Desktop, Laptop

Language

English

Subtitles

English

Level

Advanced

Effort

2 hours per week

Teaching Type

Self Paced

Video Content

2.93 hours

Course Description

Machine Learning and Data Science are exciting fields that are rapidly growing. They will give you the tools to get deeper insights from your data. This course will teach you how to create and deploy Microsoft Azure Machine Learning Studio Solutions. You'll first learn about data import, cleansing and transformation. Next, you will learn how to train, evaluate, and refine Machine Learning Models. You'll also learn how to deploy and use Predictive web services. This course will teach you how to create data science experiments with a variety machine learning algorithms. You'll also be able to code your first experiment using Jupyter notebooks or Visual Studio Code.

Course Overview

International Faculty

Case Based Learning

Post Course Interactions

Case Studies,Instructor-Moderated Discussions

Case Studies, Captstone Projects

Skills You Will Gain

What You Will Learn

Automated Machine Learning

Cleaning, Normalizing and Transforming Raw Data (Feature Engineering)

Deployment and Machine Learning Pipelines

Preparing Data and Data Sources

Training, Evaluating and Refining Machine Learning Models

Course Content

Expand all sections

Module 1: Course Overview

Module 2: Getting Started with the Azure Machine Learning Studio

Module 3: Preparing Data and Data Sources

Module 4: Cleaning, Normalizing and Transforming Raw Data (Feature Engineering)

Course Instructors

Karen Menezes

Instructor

Karen Menezes is a freelance UI developer and author who specializes in CSS. Karen works towards an open, adaptive web, and loves the implicit challenges of responsive web development where performance and user experience are indispensable.