Course Outline
Introduction
Overview of Azure Machine Learning for Government
- What is Azure Machine Learning?
- Key Features of Azure Machine Learning for Government
- Architecture of Azure Machine Learning for Government
Preparing the Machine Learning Operations Environment for Government
- Setting up an Azure Machine Learning Lab Environment for Government
Data Processing for Government
- Importing and Unzipping Data and Datasets for Government
- Transforming and Cleaning Data for Government
- Separating Training Data and Test Data for Government
Classifications and Regressions for Government
- Creating Binary and Multi-Class Models for Government
- Working with Regression Models for Government
- Tuning Hyperparameters and Parameters for Government
- Implementing Predictive and Impact Analysis for Government
- Building Decision Trees and Decision Forests for Government
Clustering for Government
- Implementing Cluster Analysis for Government
Natural Language Processing (NLP) for Government
- Featuring and Labeling Data for Government
- Using Text Analysis for Government
Recommender Systems for Government
- Working with Matchbox Recommender Models for Government
Deployment for Government
- Creating, Exposing, and Consuming Machine Learning Model Web Services for Government
Summary and Conclusion for Government
Requirements
- Experience with the Azure cloud platform for government
Audience
- Data Scientists in public sector roles
Testimonials (5)
It was very much what we asked for—and quite a balanced amount of content and exercises that covered the different profiles of the engineers in the company who participated.
Arturo Sanchez - INAIT SA
Course - Microsoft Azure Infrastructure and Deployment
Assimilable form of classes
Marek - Uniwersytet Szczecinski
Course - AZ-104T00-A: Microsoft Azure Administrator
I've got to try out resources that I've never used before.
Daniel - INIT GmbH
Course - Architecting Microsoft Azure Solutions
The Exercises
Khaled Altawallbeh - Accenture Industrial SS
Course - Azure Machine Learning (AML)
very friendly and helpful