Last month, Microsoft announced that it will host its first Data Science Summit from Sept. 26-28, 2016. The summit will offer hands-on, interactive sessions with the latest big data, machine learning and open source technologies. Joseph Sirosh, Corporate Vice President will deliver the keynote. Microsoft today announced that data visualization pioneer Edward Tufte will deliver a keynote address at the summit on the future of data analysis—and how to draw more credible conclusions from your data.
If you’re not yet familiar with Tufte’s work, take a look at his seminal book The Visual Display of Quantitative Information. It’s a breathtaking display of information design—a master class in presenting data clearly and powerfully. It’s the book that introduced and popularized many concepts that are bedrocks of data visualization today, such as small multiples and the data-ink ratio. Or check out this Washington Monthly 2011 profile, “The Information Sage,” for background on Tufte’s career and ongoing influence.
Attendees can also hear from Microsoft’s engineering and customer experts on how they can build data driven intelligent solutions, on-premises and in the cloud, with R, Python, Hadoop, Spark, and AI bots that will drive new and exciting services for their customers.
- David Smith will share ways that Microsoft is improving the lives of people around the world—and in particular, people with disabilities—by applying statistics, research, and open-source software. He’ll talk about how you can develop similar applications yourself, using the open-source R language with Microsoft advanced analytics products.
- Jennifer Marsman will speak about building intelligent applications with the Cognitive Services APIs.
- Danielle Dean will describe deploying real-world predictive maintenance solutions based on sensor data.
- Brandon Rohrer will give a live presentation of his Data Science for Absolutely Everybody series.
- Frank Seide will introduce CNTK, the Microsoft open-source, deep-learning toolkit.
- Maxim Likuyanov will share some best practices for interactive data analysis and scalable machine learning with Apache Spark.
- Rafal Lukawiecki will explain how to apply data science in a business context.
- Debraj GuhaThakurta and Max Kaznady will demonstrate statistical modeling on huge data sets with Microsoft R Server and Spark.
Registration is now open here.