Streamlining a Machine Learning Project Team
Who is this presentation for?Practicing data scientists and data engineers, CDOs with a mandate to build a team inside the organization
Artificial Intelligence is already helping many businesses become more responsive and competitive, but how do you move machine learning models efficiently from research to deployment at enterprise scale? It is imperative to plan for deployment from day one, both in tool selection and in the feedback and development process. Additionally, just as DevOps is about people working at the intersection of development and operations, there are now people working at the intersection of data science and software engineering who need to be integrated into the team with tools and support.
Sourav Day and Alex Ng explain how to streamline a machine learning project and help your machine learning engineers work as an an integrated part of your development and production teams.
- Understanding both the business problem and the data
- Containerized data science for cleaner workflows
- Data engineering as a core competency
- Building iterative data models to deliver value early
- Developing user trust in the data models
- Seamless deployment at production scale
- Observing and validating on-the-ground model use
Prerequisite knowledgeSome basic knowledge of the software engineering process and familiarity with machine learning vocabulary (model, training, etc.)
Materials or downloads needed in advance
What you'll learn
Sourav Dey is CTO at Manifold, an artificial intelligence engineering services firm with offices in Boston and Silicon Valley. Previously, Sourav led teams building data products across the technology stack, from smart thermostats and security cams at Google/Nest to power grid forecasting at AutoGrid to wireless communication chips at Qualcomm. He holds patents for his work, has been published in several IEEE journals, and has won numerous awards. He holds PhD, MS, and BS degrees in electrical engineering and computer science from MIT.
Alexander Ng is a senior data engineer at Manifold. His previous work includes a stint as engineer and technical lead doing DevOps at Kryuus as well as engineering work for the Navy. He holds a BS in electrical engineering from Boston University.
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