Ashutosh Sanzgiri (@sanzgiri) is a Data Scientist at AppNexus, the world’s largest independent Online Advertising (Ad Tech) company. I develop algorithms for machine learning products and services that help digital publishers optimize the monetization of their inventory on the AppNexus platform.
Ashutosh has a diverse educational and career background. He’s attained a Bachelor’s degree in Engineering Physics from the Indian Institute of Technology, Mumbai, a Ph.D. in Particle Physics from Texas A&M University and he’s conducted Post-Doctoral research in Nuclear Physics at Yale University. In addition to these achievements Ashutosh also has a certificate in Computational Finance and an MBA from the Oregon Health & Sciences University.
Prior to joining AppNexus, Ashutosh has held positions in Embedded Software Development, Agile Project Management, Program Management and Technical Leadership at Tektronix, Xerox, Grass Valley and Nike.
Scaling Machine Learning (ML) at your organization means increasing ML knowledge beyond the Data Science (DS) department. Several companies have Data / ML literacy strategies in place, usually through an internal data science university or a formal training program. At AppNexus, we’ve been experimenting with different ways to expand the use of ML in our products and services and share responsibility for its evaluation. An internal contest adds a competitive element, and makes the learning process more fun. It can engage people to work on a problem that’s important to the company instead of working on generic examples (e.g. “cat vs dog” classification), and gives contestants familiarity with the tools used by the DS team.
In this talk, Ashutosh will present the experience of conducting a “Kaggle-style” internal DS contest at AppNexus. he’ll discuss our motivations for doing it and how we went about it. Then he’ll share the tools we developed to host the contest. The hope being you too will find inspiration to try something in your organization!
- Manuel -> Barriers To Accelerating The Training Of Artificial Neural Networks – A Systemic Perspective
- Ashutosh -> Conducting a Data Science Contest in Your Organization
- Poul -> From Zero to Machine Learning for Everyone
- Anna -> Your First NLP Machine Learning Project: Perks and Pitfalls of Unstructured Data
- Kaleo Ha’o -> Jump or Not to Jump: Solving Flappy Bird with Deep Reinforcement Learning
- Mary & Robert -> Eliminating Machine Bias & Getting from Machine Learning Outputs to Decisions… timely things!
- Kirsten & Rich -> Now, Kirsten Westeinde & Rich Jolly
- Jon & Amy -> Say Hello to Jon and Amy @ML4ALL!
- Igor & Carol -> More @ML4ALL Intros: Meet Igor & Carol! Also, the bike ride map!
- Clair & Ricky -> @ML4ALL Meet Clair J. Sullivan & Ricky Hennessy
- Paige & Suz -> ML4ALL Speakers – Meet Paige & Suz
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