Robert Luong: Analyse prédictive dans Excel
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The document outlines the evolution and applications of cloud computing and machine learning from 2011 to 2016, highlighting a significant increase in data generation and the importance of data-driven decision-making. It discusses the capabilities of Azure Machine Learning for predictive analytics, emphasizing ease of deployment and integration with various data sources. Additionally, it provides historical context on the R programming language, its user community, and its relevance in analytics and data visualization.
Robert Luong: Analyse prédictive dans Excel
- 4. Machine Learning Churn analysis Social network analysis Recommenda- tion engines Location- based tracking and services Weather forecasting business planning Fraud detection Equipment monitoring Personalized Insurance cloud computing 2011 2016 5x increase data explosion 90% of the data in the world today has been created in the last two years alone
- 5. Action Value From data to decisions and actions
- 6. EXAMPLE SOLUTIONS Advanced Analytics scenarios
- 8. People + Data Sources Apps Sensors and devices From Data To Action On Premises INTELLIGENCEDATA ACTION Automated SystemsMicrosoft R Server & SQL R Services Apps Cortana Intelligence
- 9. Cortana Intelligence Suite Intelligence Dashboards & Visualizations Information Management Big Data Stores Machine Learning and Analytics CortanaEvent Hubs HDInsight (Hadoop and Spark) Stream Analytics Data Intelligence Action People Automated Systems Apps Web Mobile Bots Bot Framework SQL Data WarehouseData Catalog Data Lake Analytics Data Factory Machine Learning Data Lake Store Cognitive Services Power BI Data Sources Apps Sensors and devices Data
- 10. Easily build, deploy, and share predictive analytics solutions • Simple, scalable, cutting edge. A fully managed cloud service that enables you to easily build, deploy, and share predictive analytics solutions. • Deploy in minutes. Azure Machine Learning means business. You can deploy your model into production as a web service that can be called from any device, anywhere and that can use any data source. • Publish, share, monetize. Share your solution with the world in the Gallery or on the Azure Marketplace. Machine Learning and Analytics HDInsight (Hadoop and Spark) Stream Analytics Data Lake Analytics Machine Learning
- 12. 1993 Research project in Auckland, NZ 1995 Open source 1997 R-core 2000 R-1.0.0 2003 R Foundation 2004 First UseR! 2009 New York Times 2015 R-3.2.0 R Consortium Photo credit: Robert Gentleman
- 13. What is • A statistics programming language • A data visualization tool • Open source • 2.5+M users • Taught in most universities • Thriving user groups worldwide • 8000+ free algorithms in CRAN • Scalable to big data • New and recent grad’s use it Language Platform Community Ecosystem • Rich application & platform integration
- 14. IEEE Spectrum July 2015 Language Popularity IEEE Spectrum Top Programming Languages R Usage Growth Rexer Data Miner Survey, 2007-2013 Rexer Data Miner Survey #9: R
- 15. Datasize In-memory In-memory In-Memory or Disk Based Speed of Analysis Single threaded Multi-threaded Multi-threaded, parallel processing 1:N servers Support Community Community Community + Commercial Analytic Breadth & Depth 7500+ innovative analytic packages 7500+ innovative analytic packages 7500+ innovative packages + commercial parallel high-speed functions Licence Open Source Open Source Commercial license. Supported release with indemnity Copyright Microsoft Corporation. All rights reserved.
- 17. Useful links Azure ML lab: https://aka.ms/azure-ml-lab-content Azure ML Studio: https://studio.azureml.net/ Learn R: http://tryr.codeschool.com/ Free Microsoft online training: Introduction to R for Data Science: https://www.edx.org/course/introduction-r-data-science-microsoft-dat204x-3 Programming in R for Data Science: https://www.edx.org/course/programming-r-data-science-microsoft-dat209x-2 Analyzing Big Data with R server: https://www.edx.org/course/analyzing-big-data-microsoft-r-server-microsoft-dat213x Machine learning cheat sheet: https://docs.microsoft.com/en-us/azure/machine-learning/machine-learning-algorithm-cheat- sheet Spurious correlation: http://www.tylervigen.com/spurious-correlations