Jennifer Marsman
Jennifer Marsman is a Principal Developer Evangelist in Microsoft's Developer and Platform Evangelism group, where she educates developers on Microsoft's new technologies. In this role, Jennifer is a frequent speaker at software development conferences around the world. In 2016, Jennifer was recognized as one of the "top 100 most influential individuals in artificial intelligence and machine learning" by Onalytica. She has been featured in Bloomberg for her work using EEG and machine learning to perform lie detection. In 2009, Jennifer was chosen as "Techie whose innovation will have the biggest impact" by X-OLOGY for her work with GiveCamps, a weekend-long event where developers code for charity. She has also received many honors from Microsoft, including the Central Region Top Contributor Award, Heartland District Top Contributor Award, DPE Community Evangelist Award, CPE Champion Award, MSUS Diversity & Inclusion Award, and Gold Club. Prior to becoming a Developer Evangelist, Jennifer was a software developer in Microsoft's Natural Interactive Services division. In this role, she earned two patents for her work in search and data mining algorithms. Jennifer has also held positions with Ford Motor Company, National Instruments, and Soar Technology. Jennifer holds a Bachelor's Degree in Computer Engineering and Master's Degree in Computer Science and Engineering from the University of Michigan in Ann Arbor. Her graduate work specialized in artificial intelligence and computational theory. Jennifer blogs at http://blogs.msdn.com/jennifer and tweets at http://twitter.com/jennifermarsman.
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Developing for the Microsoft Band with Charles Stacy Harris IIIJennifer Marsman speaks with Charles Stacy Harris III about developing for the Microsoft Band. They discuss the capabilities of the Band: the sensors it contains, tiles, notifications, Bluetooth, haptics, and the Microsoft Health app for management. Learn how to get started with the Microsoft...
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How to Apply Deep Learning to Real-World ProblemsDeep Learning is a new area of Machine Learning research, which has been introduced with the objective of moving Machine Learning closer to one of its original goals: Artificial Intelligence.
Join Jennifer Marsman as she welcomes Sonja Knoll to the show as they take a deep dive into Deep Learning as well...
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How to Construct and Use Decision TreesDecision Trees are excellent tools for helping you to choose between several courses of action. They provide a highly effective structure within which you can lay out options and investigate the possible outcomes of choosing those options. They also help you to form a balanced picture of the risks and...
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Fun with Microsoft Cognitive ServicesMicrosoft Cognitive Services let you build apps with powerful algorithms using just a few lines of code. They work across devices and platforms such as iOS, Android, and Windows, keep improving, and are easy to set up.
Join Jennifer Marsman and Rachel Weil as they unveil some fun projects they’ve been...
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Bing Predicts: Sporting EventsBing uses search, social, and other relevant data to make intelligent predictions about upcoming events, like sporting events, reality TV shows, award shows, and political elections. In this episode, Jennifer Marsman chats with Kushal Lakhotia and Walter Sun about the machine learning that...
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Bing Predicts: Awards ShowsBing uses search, social, and other relevant data to make intelligent predictions about upcoming events, like sporting events, reality TV shows, award shows, and political elections. In this episode, Jennifer Marsman interviews Jonas Barklund and Mo Zhou about the machine learning technology that...
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Bing Predicts: Politics & ElectionsBing uses search, social, and other relevant data to make intelligent predictions about upcoming events, like sporting events, reality TV shows, award shows, and political elections. In this episode, Jennifer Marsman and Gene Vaatveit discuss the machine learning technology behind predicting...
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Bing Predicts: Reality TVBing uses search, social, and other relevant data to make intelligent predictions about upcoming events, like sporting events, reality TV shows, award shows, and political elections. In this episode, Jennifer Marsman speaks to Sundar Rajan and Jonas Barklund about the machine learning behind...
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Bing Predicts: How It BeganBing uses search, social, and other relevant data to make intelligent predictions about upcoming events, like sporting events, reality TV shows, award shows, and political elections. In this episode, Jennifer Marsman and Walter Sun (founder of Bing Predicts) discuss how the Bing Predicts team...
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Live from Build 2016: Cognitive ServicesIn this video, Jennifer Marsman talks with Anna Roth about Microsoft Cognitive services.
Learn a little about the underlying technology behind the emotion recognition APIs, hear some ideas about how to use them in your apps, and watch Jennifer and Anna make funny faces to get the API to detect different...
Staff
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Our Reaction to the News and Announcements Made at Build 2016
May 09, 2016 at 8:37PM@Doctor Who: I have Skype version 7.22.0.109. I see 3 options: a paper clip button to attach something, an emoticon button, and the send button. I click the paper clip button (which expands into several options) and then click another camera button to send an image.
How Azure ML Helped Predict the Results of the NCAA "March Madness" Tournament
Mar 14, 2016 at 12:58PM@Francesco: Unfortunately, the experiment Damon walk through is not published online.
@David Blundell: My apologies. AzureML is Azure Machine Learning, a tool that allows you to perform enterprise-quality machine learning from a browser. The documentation is at https://azure.microsoft.com/en-us/documentation/services/machine-learning/. "March Madness" is a college basketball tournament that happens every year in March in the United States. It is known for having great upsets (a low-ranked team beating a high-ranked team) so it's popular to create a bracket to predict who will win and proceed to the next level of the tournament. More information at https://en.wikipedia.org/wiki/NCAA_Men%27s_Division_I_Basketball_Championship.
@eugenio: Gracias!
Creating a Silverlight Blog Badge, Part 1: Animation to Catch the Eye
Jun 05, 2009 at 7:57PMThe conclusion of this webcast series is posted now: http://channel9.msdn.com/posts/jennmar/Creating-a-Silverlight-Blog-Badge-Part-2-Countdown-Calendar/.