Introduction to Microsoft Azure machine learning Studio and Services

Questions you will answer in this workshop

Learning Objectives

• Learn the difference between Artificial Intelligence, Machine Learning and Deep learning
• Learn how to perform machine learning without any code!
• See model training, tuning and deployment LIVE In the CLOUD!
• Learn the process of loading and preparing data for training
• Experiment with Azure ML Studio and Machine Learning Services

What will I learn during this workshop

Prequisites

While you won't need prior experience in practical machine learning or with Microsoft Azure to follow along with this class, we'll assume some familiarity with:

• Python programming language: See Udacity - Intro to Python

Steps

This workshop consists of N activities:

Flow

1. Clone this git repository using git clone https://github.com/beginners-machine-learning-london/intro_to_Azure_ml_studio_and_services
2. Create an Azure account

IMPORTANT NOTE: Make sure to shut down your Azure notebook instances and workspaces after you are done. Otherwise, you will get charged for it per hour. It will not shut down automatically. For training, you will provision a new instance, however that second instance will stop running after the training job is finished.

Featured technologies

• Python: Python is a programming language that lets you work more quickly and integrate your systems more effectively.
• Azure ML Studio: Azure Machine Learning Studio is a GUI-based integrated development environment for constructing and operationalizing Machine Learning workflow on Azure.

Dataset Source

The dataset for this workshop can be obtained via UCI. However, a static copy is also provided in the exercises/data folder. You can download the dataset from UCI

Learn More

• Getting Started with Azure Machine Learning | Pluralsight: Enjoyed this workshop? The content was inspired from Pluralsight's Getting Started with Azure Machine Learning course.
• A-Z list of Machine Learning Studio modules: This article provides an alphabetised list of the modules that are available in Azure Machine Learning Studio.
• Machine learning algorithm cheat sheet for Azure Machine Learning Studio: The Azure Machine Learning Studio Algorithm Cheat Sheet helps you choose the right algorithm for a predictive analytics model.
• Machine learning basics with algorithm examples: Download this easy-to-understand infographic overview of machine learning basics to learn about popular algorithms used to answer common machine learning questions.
• Deploy an Azure Machine Learning Studio web service: Azure Machine Learning Studio enables you to build and test a predictive analytic solution. Learn here how you can deploy your trained models as a web service.
• Retrain and deploy a machine learning model: Retraining is one way to ensure machine learning models stay accurate and based on the most relevant data available. This article shows how to retrain and deploy a machine learning model as a new web service in Studio.
• Retraining an Azure Machine Learning Application:You can programmatically retrain an Azure Machine Learning Web Service thereby improving the predictions of your predictive applications.

Collaboration, Questions and Discussions

• BML Slack Channel - Join our slack workspace to collaborate with others, discuss ideas and post any questions you have about our group or the workshops
• Have questions about workshop exercises or setting up your AWS account and configurations? Post them here

Workshop Feedback

• How was this workshop? Please provide us with some feedback here so that we can improve the content and delivery of future workshops.