Azure Machine Learning

Azure Machine learning presentation, at Microsoft Ventures Paris

Transcript

1. Azure Machine Learning 22 Juillet 2014
2. intelligence will become ambient intelligence from machine learning
3. IPYTHON http://3-4.fr/azure-ipython-wye
4. Delivering on one of the old dreams of Microsoft co-founder Bill Gates: Computers that can see, hear and understand. John Platt Distinguished scientist at Microsoft Research What is Machine Learning? Computing systems that improve with experience “ ”
5. SQL Server enables data mining of databases Computers work on users behalf, filtering junk email Microsoft Kinect can watch users gestures Microsoft launches Azure Machine Learning, making years of innovation available Microsoft search engine built with machine learning Bing Maps ships with ML traffic- prediction service Successful, real-time, speech-to- speech translation Microsoft & Machine Learning 20 years of realizing innovation John Platt, Distinguished scientist at Microsoft Research 1999 2012 2008 2004 2014 2010 2005 Machine learning is pervasive throughout Microsoft products. “ ”
6. Break away from industry limitations Huge set-up costs create unnecessary barriers to entry Siloed and cumbersome data management restricts access to data Complex and fragmented tools limit participation in exploring data and building predictive models Many models never achieve business value due to difficulties with deploying to production
7. ML Studio and the Data Scientist • Access and prepare data • Create, test and train models • Collaborate • One click to stage for production via the API service Business users easily access results: from anywhere, on any device HDInsight Desktop Data Azure Storage Mobile Apps PowerBI/ Dashboards Web Apps ML API service and the Developer • Tested models available as an url that can be called from any end point Azure Portal & ML API service and the Azure Ops Team • Create ML Studio workspace • Assign storage account(s) • Monitor ML consumption • See alerts when model is ready • Deploy models to web service
8. HELLO WORLD
9. Easily manage and monitor Ensure enterprise- grade security Amplify your investments Operationalize in minutes Streamline with one portal to view and update Peace of mind with best-in-class data and identity security features Get more from your machine learning and Azure solutions Tooled for quick deployment, hand-off and updates
10. Azure Machine Learning in action Real world examples “There was zero percent chance we were going to take a step backwards and consider a machine learning solution that wasn’t well-established and proven effective in the cloud. Kristian Kimbro Rickard MAX451 ”
11. The ease of implementation makes machine learning accessible to a larger number of investigators with various backgrounds—even non-data scientists. Bertrand Lasternas Carnegie Mellon Smart Buildings The Center for Building Performance and Diagnostics uses weather forecasts, real-time temperature reads, and behavioral research data to optimize building heating and cooling systems in real-time. Key Benefits • User friendly set up and integration with existing systems • Seamless data handling • Accessible and easy to use across backgrounds • Quickly compare algorithms “ ”
12. The standout benefit for us was to quickly build and test predictive models and verify their results. There is no cognitive overhead to learn new scripting or coding language. Yogesh Dandawate Icertis Applied Cloud Investment Optimization Icertis, a cloud solutions provider, built a predictive model using past performance data to determine the optimal locations for its clients to build new retail stores. Key Benefits • Quickly build, test and verify models • No new scripting or coding languages • Easily import and modify algorithms developed outside the solution “ ”
13. Imagine what machine learning could do for your business. Churn analysis Equipment monitoring Spam filtering Ad targeting Recommendations Fraud detection Image detection & classification Forecasting Anomaly detection
14. Learn more and sign up for a free trial of Azure azure.com/ml “Azure ML is the future of Analytics. It seamlessly brings together statistics/mathematics with ML, AI, and advances in data storage and computing. Corey Coscioni West Monroe Partners, LLC ”
15. ANALYSE DE SENTIMENTS
16. • http://azure.microsoft.com/en- us/pricing/details/machine-learning/ Pricing
17. QUELQUES EXPÉRIMENTATIONS EXEMPLES (copies d’écrans en annexes)
18. Appendix
19. Regression
20. Regression
21. Classification
22. Classification (binary)
23. Classification (multiclass)
24. Clustering
25. Clustering
26. Clustering
27. Recommandations
28. Run History
29. Cross Validation
30. Sweep Parameters
31. Key Capabilities
32. Key Capabilities
33. Key Capabilities
34. Key Capabilities
35. Easily manage and monitor Streamline with one portal to view and update Ensure enterprise- grade security Peace of mind with best-in- class data and identity security features Amplify your investments Get more from you machine learning and Azure solutions Operationalize in minutes Tooled for quick deployment, hand-off and updates Set up an Azure subscription in seconds with the help of a set-up Wizard Quickly enable data scientists by creating MLStudio workspaces assigned by Windows Live ID Predict expenses by monitoring storage and CPU usage of workspaces and web services with a near real-time view Receive alerts when a model is ready for production or update Provide data access only to those who need it with unique storage account keys Securely scale to tackle the largest datasets Control access with Azure’s best-in- class identity management solution Leverage, extend and share proprietary models Access business-tested algorithms from Microsoft—including those that power Bing and Xbox Boost data scientist productivity by providing time-saving tools and enabling collaboration Gain new insights on existing Azure data Deploy tested models to production with one click Quickly share results with business users—from anywhere on any device Receive alerts when a new or replacement model is ready Easily share web services with developers by providing a url
36. Data Scientist message • Access, prepare and visualize the data in one place • Access the training set and size you need with HDInsight • Import datasets right from your desktop into your Studio storage account • Easily prepare and visualize data • Choose your own Studio experience • Choose from a library of modules, or write your own solution with R • Securely mix and match your proprietary work with business-tested Microsoft algorithms • Easily share your workspace inside your organization or around the world • Build on your company’s private immutable model library • Test effectiveness of to 10 models simultaneously • Operationalize and update models in minutes • Transition seamlessly from model to cloud web service with just 3 clicks • Retrain and update models on-demand
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