Explore the fundamentals of Azure Machine Learning Studio and predictive analytics in this comprehensive 59-minute conference talk. Learn how to create Azure ML experiments, implement various data manipulation techniques, and customize machine learning processes using R modules. Discover the process of publishing and consuming endpoints for predictive analysis, as well as retraining ML models. Gain insights into unsupervised learning workflows, decision trees, and accuracy evaluation. Understand how to leverage Azure ML for low-cost, easy-to-use, and scalable machine learning solutions that can enhance business applications with intelligent predictions. By the end of this talk, acquire the knowledge to use diverse data sources, create experiments, and implement predictions in your systems, enabling you to enrich your applications with data-driven insights using proven ML technologies.
Predicting the Future as a Service with Azure ML and R
Overview
Syllabus
Introduction
Agenda
What is machine learning
How machine learning works
How human brain works
Unsupervised learning
Unsupervised learning workflow
You need to know your stuff
What is Azure ML
Demo
New Experiment
Split Data
Train Model
Score Model
Predicted Labels
Evaluate Model
Run Model
Decision Tree
Accuracy
Machine Learning
Scripts
Why use Azure ML
What does it do
Web Services
Cortana
Twitter Sentiment
Text Data
Summary
Taught by
NDC Conferences
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