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The United States Postal Service processed over 150 billion pieces of mail in 2013—far too much for efficient human sorting. But as recently as 1997,

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Presentation on theme: "The United States Postal Service processed over 150 billion pieces of mail in 2013—far too much for efficient human sorting. But as recently as 1997,"— Presentation transcript:

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3 The United States Postal Service processed over 150 billion pieces of mail in 2013—far too much for efficient human sorting. But as recently as 1997, only 10% of hand-addressed mail was successfully sorted automatically.

4 The challenge in automation is enabling computers to interpret endless variation in handwriting.

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6 By providing feedback, the Postal Service was able to train computers to accurately read human handwriting. Today, with the help of machine learning, over 98% of all mail is successfully processed by machines.

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8 Vision Analytics Recommenda- tion engines Advertising analysis Weather forecasting for business planning Social network analysis Legal discovery and document archiving Pricing analysis Fraud detection Churn analysis Equipment monitoring Location-based tracking and services Personalized Insurance Imagine what Machine Learning could do to your business

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10 Bing maps launches What’s the best way home? Microsoft Research formed Kinect launches What does that motion “mean”? Azure Machine Learning launches What will happen next? Hotmail launches Which email is junk? Bing search launches Which searches are most relevant? Skype Translator launches What is that person saying? Microsoft & Machine Learning Answering questions with experience 1991201420091997201420102008 “Azure Machine Learning offers a data science experience that is directly accessible to business analysts and domain experts, reducing complexity and broadening participation through better tooling.” Hans Kristiansen Capgemini

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12 Fully managed Intuitive Best in Class Algorithms + R + Python Deploy in minutes No software to install, no hardware to manage, and one portal to view and update Simple drag, drop and connect interface for both data acquisition and modeling Access to sample experiments, tested algorithms, support for your custom R, and over 350 R packages Tooled for quick deployment, hand-off and updates – click “Publish Web Service”

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14 ML Apps Marketplace ML Operationalization ML Studio ML Algorithms Azure ML Marketplace Producer Consumer

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17 Thank you! azure.com/ml “ Microsoft has a solid track record for creating user- friendly tools, and Pier 1 is helping prove Microsoft can take something as complex as machine learning and make it accessible via the cloud Andy Laudato Pier 1 Imports ”


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