This course is designed to introduce the participant to the exciting world of predictive analytics built using drag-and-drop with Microsoft Azure Machine Learning Studio, all without coding from your desktop, using your browser. The course is targeted towards business analysts, business intelligence developers, and managers interesting in exploring the world of predictive analytics for use as a competitive tool.
Erfarenhet av att arbeta med affärsdata. Grundläggande kunskaper om datastrukturer, antingen i Microsoft Excel eller i relationsdatabaser såsom exempelvis Oracle Database eller SQL Server.
What is Machine Learning?
In this module, we will explain machine learning and the concepts behind it.
- One Methodology
- Supervised vs. Unsupervised Methods
- Analytics Spectrum
- Development Methodology with Azure Machine Learning Studio
- Be Very Vigilant
Introduction to Azure Machine Learning Studio
In this module, we will explore the Azure Machine Learning Studio interface and walk through the options available.
- Web Services
- Trained Models
- Walkthrough Exercise and Group Discussions
In this module, we will cover the steps necessary for data cleaning and explore other data preparation techniques.
- Tools for Cleaning
- Text Files vs. Binary Files
- Structures of Data
- Steps for Data Cleaning
- Common Cleaning Tasks
- Feature Selection
- Feature Engineering
- Group Discussion
Machine Learning Algorithms
In this module, we will explain the different types of algorithms available and their uses.
- Anomaly Detection
- Azure Machine Learning Cheat Sheet
- Group Discussion and Exercises
Building Models - Exercises
In this module, we explore the topic of customer propensity (inclinations and tendencies) and how to use Machine Learning to help with this common business question. This is an exercise module which contains both instructor-led and individual exercises.
- Group Discussion 1: Data Acquisition
- Group Discussion 2: Data Preparation
- Group Discussion 3: Feature Selection
- Group Discussion 4: Train Data
- Group Discussion 5: Cross Validation and Comparing Regressions
- Group Discussion 6: Results
- Group Discussion: Evaluate the Solutions – Learn from Examples
Visualizing Analytical Models with Power BI
In this module, we will explore the visualizations and options available using Power BI.
- What is Power BI?
- Creating a Power BI Account
- Deploying to Power BI