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There can be little doubt that the single hottest career in the data field is the data scientist or BI developer skilled in predictive analytics.
Yes, Big Data is on everyone’s lips but what happens after that big data is ingested into a data lake?
The answer is predictive analytics.
Because we live in the big data era, machine learning has become much more popular in the last few years.
Having lots of data to work with in many different areas lets the techniques of machine learning be applied to a broader set of problems.
Data can hold secrets, especially if you have lots of it.
With lots of data about something, you can examine that data in intelligent ways to find patterns.
This is exactly what machine learning does: It examines large amounts of data looking for patterns, then generates code that lets you recognize those patterns in new data.
Your applications can use this generated code to make better predictions. In other words, machine learning can help you create smarter applications.
Azure Machine Learning (Azure ML) is a cloud service that helps people execute the machine learning process.
As its name suggests, it runs on Microsoft Azure, a public cloud platform.
Because of this, Azure ML can work with very large amounts of data and be accessed from anywhere in the world. Using it requires just a web browser and an internet connection.
In this course you will be learning and building predictive algorithms using Azure Machine Learning Studio.
At the end of this course you’ll be able to build and evaluate a binary classification predictive model without authoring a single line of code
You’ll build an Experiment for a targeted email campaigned and be able to tell what customers should receive flyers and those that shouldn’t.
Thanks for reading about Azure Machine Learning Studio and I’ll see you in the course.
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