State of Data Science & Machine Learning
Submitted by Peter Wang (@pwang) on Wednesday, 19 June 2019
Session type: Full talk of 40 mins Status: Confirmed & Scheduled
As machine learning and AI become adopted at an increasing rate, businesses and practitioners face new types of challenges. At the heart of many of these lies an uncomfortable truth: that data science is not merely a new kind of technical specialty, but rather that it represents an opportunity for deep business transformation. In this talk, Peter speaks to this concept that Data Science isn’t just a “job”, it’s actually a democratization of empiricism. Furthermore, the idea of “democratization” is intertwined with the role of Open Source in innovation, and the kind of ethical future that we create around machine learning and AI.
- Data science is not just a job
- operationalization vs. exploration
- democratization, “citizen” data science
- The role and future of open source
- Two types of OSS
- Software isn’t just code
- Crowdsourcing innovation
- What comes next?
- Hardware innovation
- Desegregating computing
- The coming age of inference engines
Peter Wang is a co-founder of Anaconda, Inc., where he is CTO and leads the Open Source and Community Innovation team. He has been developing commercial scientific computing and visualization software for 20 years. He has extensive experience in software design and development across a broad range of areas, including 3D graphics, geophysics, large data simulation and visualization, financial risk modeling, and medical imaging.
As a creator of the PyData community and conferences, he devotes time and energy to growing the Python data science community and advocating and teaching Python at conferences around the world. Peter holds a BA in Physics from Cornell University.