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https://aka.ms/cs492
Who is he?
Detection Result:
JSON:
[
{
"faceRectangle": {
"width": 109,
"height": 109,
"left": 62,
"top": 62
},
"attributes": {
"age"...
Verification Result:
JSON:
[
{
"isIdentical":false,
"confidence":0.01
}
]
• Customers
• Fast food +
• Retail
• School food
• Hotel
• Catering
• Year 2014
• 8 subsidiary
• 60,000 customers
• 4,500 ...
• top 20% churn prediction
3x more revenue(Prev.
random)
• 200+ churn prediction,
45% prevent user = 17%
churn
JJ Food Ser...
The United States Postal Service
processed over 150 billion pieces of
mail in 2013—far too much for
efficient human sortin...
challenge
Learning various hand-writing and
recognize
- 98%+ accuracy
Descriptive
Analytics
Diagnostic
Analytics
Predictive
Analytics
Prescriptive
Analytics
What
happened?
Why did
it happen?
W...
Machine learning
DEMO – building training model
Make machine learning accessible to every
enterprise, data scientist, developer,
information worker, consumer, and device
...
Machine Learning developer in Business
Machine Learning developer in Business
Machine Learning developer in Business
Machine Learning developer in Business
Machine Learning developer in Business
Machine Learning developer in Business
Machine Learning developer in Business
Machine Learning developer in Business
Machine Learning developer in Business
Machine Learning developer in Business
Machine Learning developer in Business
Machine Learning developer in Business
Machine Learning developer in Business
Machine Learning developer in Business
Machine Learning developer in Business
Machine Learning developer in Business
Machine Learning developer in Business
Machine Learning developer in Business
Machine Learning developer in Business
Machine Learning developer in Business
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Machine Learning developer in Business

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Presentation document for kaist CS492 class - 20161103 Session subject :
Machine Learning developer in "Business"
-People using ML in business (10 min)
-Machine Learning subsets including Deep Learning Toolkit CNTK and Tensorflow (20 min)
-Building predictive model & deploy in Azure Machine Learning (20 min)
-Q&A (10 min)

Published in: Data & Analytics
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Machine Learning developer in Business

  1. 1. https://aka.ms/cs492
  2. 2. Who is he?
  3. 3. Detection Result: JSON: [ { "faceRectangle": { "width": 109, "height": 109, "left": 62, "top": 62 }, "attributes": { "age": 31, "gender": "male", "headPose": { "roll": "2.9", "yaw": "-1.3", "pitch": "0.0" } "faceLandmarks": { "pupilLeft": { "x": "93.6", "y": "88.2" }, "pupilRight": { "x": "138.4", "y": "91.7" }, ...
  4. 4. Verification Result: JSON: [ { "isIdentical":false, "confidence":0.01 } ]
  5. 5. • Customers • Fast food + • Retail • School food • Hotel • Catering • Year 2014 • 8 subsidiary • 60,000 customers • 4,500 products • 1M + purchase orders JJ Food Service
  6. 6. • top 20% churn prediction 3x more revenue(Prev. random) • 200+ churn prediction, 45% prevent user = 17% churn JJ Food Service
  7. 7. 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.
  8. 8. challenge
  9. 9. Learning various hand-writing and recognize - 98%+ accuracy
  10. 10. Descriptive Analytics Diagnostic Analytics Predictive Analytics Prescriptive Analytics What happened? Why did it happen? What will happen? How can we make it happen? Traditional BI Advanced Analytics
  11. 11. Machine learning DEMO – building training model
  12. 12. Make machine learning accessible to every enterprise, data scientist, developer, information worker, consumer, and device anywhere in the world. Azure Machine Learning target

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