Skip to main content

Machine Learning Pipelines with Azure ML Studio

 

Machine Learning Pipelines with Azure ML Studio

Duration: 2 hours

What You’ll Learn:

  • 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
  • Showcase this hands-on experience in an interview

Enroll Now

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. It predicts whether an individual's annual income is greater than or less than $50,000. The estimator used in this project is a Two-Class Boosted Decision Tree classifier. Some of the features used to train the model are age, education, occupation, etc. Once you have scored and evaluated the model on the test data, you will deploy the trained model as an Azure Machine Learning web service. In just under an hour, you will be able to send new data to the web service API and receive the resulting predictions. This is the second course in this series on building machine learning applications using Azure Machine Learning Studio. I highly encourage you to take the first course before proceeding. It has instructions on how to set up your Azure ML account with $200 worth of free credit to get started with running your experiments! This course runs on Coursera's hands-on project platform called Rhyme. On Rhyme, you do projects in a hands-on manner in your browser. You will get instant access to pre-configured cloud desktops containing all of the software and data you need for the project. Everything is already set up directly in your internet browser so you can just focus on learning. For this project, you’ll get instant access to a cloud desktop with Python, Jupyter, and scikit-learn pre-installed. Notes: - You will be able to access the cloud desktop 5 times. However, you will be able to access instructions videos as many times as you want. - This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

Requirements

A basic understanding of machine learning workflows.

SKILLS YOU WILL DEVELOP

Data ScienceMachine LearningData AnalysisBinary ClassificationAzure Machine Learning

Learn step-by-step

In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:

  1. Introduction and Project Overview

  2. Data Cleaning

  3. Accounting for Class Imbalance

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

  5. Scoring and Evaluating the Models

  6. Publishing the Trained Model as a Web Service for Inference


Labels:

Comments

Post a Comment

Popular posts from this blog

Azure Synapse SQL Pool – Implement Polybase

  Azure Synapse SQL Pool – Implement Polybase Duration:  2 hours Intermediate No download needed Split-screen video English Desktop only What You’ll Learn: Create Azure SQL Pool Create Azure Data Lake Storage Gen2 Configure and Implement Polybase Showcase this hands-on experience in an interview Enroll Now Also Read:  IIT Kharagpur Free Courses on Introduction to  Machine Learning In this 1-hour long project-based course, you will learn how to implement Polybase in Azure Synapse SQL Pool. In this project, we are going to see how to implement Polybase in Azure Synapse SQL Pool. Polybase in simple words is, a feature provided by Azure SQL Pool through which you can access the data stored in Azure Data Lake Storage/Blob/HDFS using a SQL interface to access the files stored in above mentioned storage systems. Basically, you can execute SQL queries on the files containing the data. To implement Polybase the source that we are considering is a text file stored in Azure Data Lake Sto
Post a Comment
Read more

English for Personal and Professional Development

  English for Personal and Professional Development DETAILS English for Personal and Professional Development Language English Certification Yes Duration 21 Hours The course is designed to give you the tools you need to improve your communication skills and the best strategies for using them to your advantage. ENROLL FOR FREE! COURSE DESCRIPTION Do you struggle when you communicate in English? Do you feel short of words and confidence when it comes to public speaking? Do you struggle with words and expressions when you draft a letter and an email? If you answer yes to any of the above, you can rely on this course. The course is designed to give you both the tools you need to improve your communication skills, and the most successful strategies for using them to your advantage. It is a combination of communication skills, grammar and soft skills which gives it an edge over other courses. The icing on the cake is the bilingual method through which concepts have been elaborated. The cours
Post a Comment
Read more

IIT Kharagpur Free Courses on Introduction to Machine Learning

  Hello Learner, this post is to inform you about that IIT Kharagpur (Indian Institute of Technology, Kharagpur) Offers Premium Online Course For Free. IIT Madras launching a fresh course “ Introduction to Machine Learning ” Enrollments are now  open  for this course.  Course Description This course provides a concise introduction to the fundamental concepts in machine learning and popular machine learning algorithms. We will cover the standard and most popular supervised learning algorithms including linear regression, logistic regression, decision trees, k-nearest neighbour, an introduction to Bayesian learning and the naïve Bayes algorithm, support vector machines and kernels and neural networks with an introduction to Deep Learning. We will also cover the basic clustering algorithms. Feature reduction methods will also be discussed. We will introduce the basics of computational learning theory. In the course we will discuss various issues related to the application of machine learn
Post a Comment
Read more