Machine Learning Pipelines with Azure ML Studio

4.5 /5

(4 Ratings)

Offered byCoursera
Public/Government Institute

Machine Learning Pipelines with Azure ML Studio
at
Coursera
Overview

Learn everything you need to know about Machine Learning and give a boost to your professional career

Duration	2 hours
Mode of learning	Online
Schedule type	Self paced
Difficulty level	Beginner
Credential	Certificate

Machine Learning Pipelines with Azure ML Studio

Table of contents

Overview
Course Details
Curriculum
Faculty
Entry Requirements
+ 1 more item

Machine Learning Pipelines with Azure ML Studio
at
Coursera
Course details

Skills you will learn

Microsoft Azure Accounting

What are the course deliverables?

Pre-process data using appropriate modules
Train and evaluate a boosted decision tree model on Azure ML Studio
Create scoring and predictive experiments
Deploy the trained model as an Azure web service

More about this course

In this project-based course, you are going to build an end-to-end machine learning pipeline in Azure ML Studio, all without writing a single line of code
This course uses the Adult Income Census data set to train a model to predict an individual's income
This is the second course in this series on building machine learning applications using Azure Machine Learning Studio
You will get instant access to pre-configured cloud desktops containing all of the software and data you need for the project

Machine Learning Pipelines with Azure ML Studio
at
Coursera
Curriculum

Introduction and Project Overview

Data Cleaning

Accounting for Class Imbalance

Training a Two-Class Boosted Decision Tree Model and Hyperparameter Tuning

Scoring and Evaluating the Models

Publishing the Trained Model as a Web Service for Inference

Machine Learning Pipelines with Azure ML Studio
at
Coursera
Faculty details

Snehan Kekre

Snehan Kekre is a Developer Advocate at Snowflake, where he specializes in the Streamlit open-source Python library. In the past, he has worked for Streamlit (pre-acquisition) as a Developer Advocate , and has authored and taught over 40+ guided projects on machine learning and data science at Coursera.