The Microsoft Azure Machine Learning automated data pipeline cheat sheet helps you navigate through thetechnology you can use to get your data to your Machine Learning web service where it can be scored by your predictive analytics model.
This Cheat Sheet gives you a peek at these tools and shows you how they fit in to the broader context of data science. Seeing What You Need to Know When Getting Started in Data Science Traditionally, big data is the term for data that has incredible volume, velocity, and variety. Data science is a multi-disciplinary field. Thus, there are thousands of packages and hundreds of programming functions out there in the data science world! An aspiring data enthusiast need not know all. A cheat sheet or reference card is a compilation of.
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- The cheatsheet is loosely based off of The Data Science Design Manual by Steven S. Skiena and An Introduction to Statistical Learning by Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani. Inspired by William Chen's The Only Probability Cheatsheet You'll Ever Need, located here. Full cheat sheet.
Depending on whether your data is on-premises, in the cloud, or real-time streaming, there are different mechanisms available to move the data to your web service endpoint for scoring.This cheat sheet walks you through the decisions you need to make, and it offers links to articles that can help you develop your solution.
Download the Machine Learning automated data pipeline cheat sheet
Once you download the cheat sheet, you can print it in tabloid size (11 x 17 in.).
Download the cheat sheet here: Microsoft Azure Machine Learning automated data pipeline cheat sheet
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- For an overview of Microsoft Azure Machine Learning, see Introduction to machine learning on Microsoft Azure.
- For an explanation of how to deploy a scoring web service, see Deploy an Azure Machine Learning web service.
- For a discussion of how to consume a scoring web service, see How to consume an Azure Machine Learning Web service.