How We Share Machine Learning, Analytics & Data Science at Microsoft

We recently concluded the Fall 2016 edition of the Machine Learning, Analytics & Data Science (MLADS) conference, Microsoft’s largest internal gathering of employees focused on this very important field. This latest edition was the sixth in a very popular series that we launched in spring 2014, and with over 3,000 employees participating over the course of this two-day event in Redmond, it was a testimony to the rapid growth of this community at Microsoft and the expanding investments that Microsoft is making in this area.

The conference itself is just one aspect of the very large community that we are fostering within the company, many thousands strong, who are unified by their passion for this space and its potential for customer impact, and their desire to network and learn from one another. We drive a twice a year call for content from the community, and the submissions from that process feed into the final MLADS conference programs.

The latest conference featured over 100 tutorials and talks, covering the whole gamut of topics including Big Data platforms such as Azure Data Lake, Deep Learning tools and techniques, including the Cognitive Toolkit (Microsoft’s Open Source Deep Learning Framework), the Microsoft Bot Framework, commonly used techniques such as Classification, Regression, Time Series, Anomaly Detection and more, Security Analytics, R, Python, free hosted Jupyter notebooks and much more. There was even a hands-on tutorial offered on Julia, taught by one of the co-founders of that language. Additionally, there were over 60 demos and posters showcased at our evening MLADS reception. Attendees also availed themselves of 1:1 consultation sessions with expert ML engineers and data scientists, to get their questions answered.


A panel of judges shortlisted the top submissions for our Distinguished Contribution Awards, a unique internal recognition program for top-class work being done in this field. Additionally, selective conference submissions were also chosen for publication in our internal Microsoft Journal of Applied Research. The latest conference also featured several external speakers, including presenters from University of Washington, Julia Computing, Algorithmia and NASA, and also included informal lunchtime meetups on important related efforts such as Women in Machine Learning, Women in Data Science, Ethics in Machine Learning and Microsoft Professional Programs in Data Science.

We opened to packed keynote sessions each day of the conference: Christopher Bishop, Distinguished Scientist and Director of the Microsoft Cambridge (UK) Labs, talked about Embracing Uncertainty, highlighting how fundamental uncertainty is to the entire ML/AI revolution, and thus the need for mathematical rigor around probability and decision making, to ensure that predictions offered by software systems maximize the value created for customers and users.

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Christopher Bishop, Distinguished Scientist and Director of the Microsoft Cambridge (UK) Labs

Joseph Sirosh, Corporate Vice President of the Data Group at Microsoft, used his keynote to highlight the massive impact that the Intelligent Cloud is having on the human condition. Joseph’s talk covered three key design patterns for creating intelligent apps, namely: Intelligent Databases, Intelligent Data Lakes, and Deep Intelligence, and included demos illustrating these patterns based on Microsoft’s partnerships with top companies such as Stack Overflow, Uber, Lowe’s, eSmart Systems and the LV Prasad Eye Institute.

Additionally, Xuedong Huang (XD), Distinguished Engineer, talked about the Cognitive Toolkit (formerly CNTK), including an impressive demo of real-time captioning of his own talk, enabled by the breakthrough technology that his team is creating in the realm of speech recognition.


Xuedong Huang, Distinguished Engineer, Microsoft

The conference was book-ended by a Startup Showcase, at which employees were able to connect with founders and engineers from the latest cohort of startups that are part of the Microsoft Accelerator program in Seattle, and a closing plenary panel on the very important topic of Privacy, Ethics & Machine Learning.

Between our large MLADS conferences, our community also has a regular cadence of in-person and online events, including quarterly ML-focused hackathons. Through these investments, practitioners from across the global Microsoft community are able to share knowledge, help each another and enhance Microsoft’s products and services through the power of cutting-edge techniques in big data, ML, advanced analytics and data science.

CIML Blog Team
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