Track Overview
ML Everywhere
ML is pervasive and affects different verticals in the economy, from sales operations, to forecasting applications, marketing campaigns, and healthcare systems. ML is really transforming the world around us, creating an avenue to innovation across all sectors of the global economy. In this track you will learn all about the latest ML innovations and the multiple fields where and how ML is being applied and deployed: in particular, you will learn about ML operations (MLOps) to accelerate AI adoption and the latest open-source frameworks for improving real-world ML applications.
From this track
What You Should Know Before Deploying ML in Production
Tuesday Nov 9 / 11:10AM EST
MLOps provides tools that make building, deploying, and maintaining machine learning solutions easier than ever before. However, MLOps is not only a static set of tools that defines the way you operationalize your machine learning models, but is also (and most importantly) about your organization...
Francesca Lazzeri
Principal Data Scientist Manager @Microsoft
The Unreasonable Effectiveness of Zero Shot Learning
Tuesday Nov 9 / 12:10PM EST
A long and expensive phase of machine learning projects is collecting and labelling data, and training ML models. In this talk I will show how one can get started deploying models without requiring any data. We talk about what foundational models are, and go through examples of them, such as...
Roland Meertens
Product Manager @annotell
Streaming-first Infrastructure for Real-time ML
Tuesday Nov 9 / 01:10PM EST
Because of data drift, the accuracy of an ML model degrades over time. How well a model performs depends on how often it’s updated. While companies like Alibaba, ByteDance, Google, Facebook have been able to leverage real-time pipelines to continually update many of their models in...
Chip Huyen
Founder at stealth startup & Teaching ML Sys @Stanford
ML Panel: "ML in Production - What's Next?"
Tuesday Nov 9 / 02:10PM EST
The panel will discuss the current lessons learned with putting ML systems into production.What is working and what is not working, from building ML teams, dealing with large datasets, governance and ethics/privacy issues, and what's around the corner for production ML, and ML in computing...
Chip Huyen
Founder at stealth startup & Teaching ML Sys @Stanford
Shijing Fang
Principal Data Scientist @Microsoft
Vernon Germano
Senior Manager of Machine Learning Engineering @zillow
Speakers from this track
Francesca Lazzeri
Principal Data Scientist Manager @Microsoft
Francesca Lazzeri, PhD is an experienced scientist and machine learning practitioner with over 12 years of both academic and industry experience. She is author of the book “Machine Learning for Time Series Forecasting with Python” (Wiley) and many other publications, including...
Read moreFind Francesca Lazzeri at:
Roland Meertens
Product Manager @annotell
Roland has a passion for Artificial Intelligence, and is specialised in robotics projects. He set up machine learning projects all the way from sensor selection, data collection and labelling to deploying the model in production. Please approach him to talk about deep learning and neural networks.
Read more
Chip Huyen
Founder at stealth startup & Teaching ML Sys @Stanford
Chip Huyen is an engineer and founder working to develop tools for ML models to continually learn in production. Through her work with Snorkel AI, NVIDIA, and Netflix, she has helped some of the world’s largest organizations deploy machine learning systems. She teaches Machine Learning...
Read moreFind Chip Huyen at:
Shijing Fang
Principal Data Scientist @Microsoft
Shijing Fang is the Principal Data Scientist at Microsoft. With fifteen years of industrial experience as data scientist, Shijing has been influencing business decisions to improve customer product experience, lifetime value, and investment ROI through data analysis, market competitive...
Read moreFind Shijing Fang at:
Vernon Germano
Senior Manager of Machine Learning Engineering @zillow
Vernon Germano is a Sr Manager of Machine Learning Engineering for Zillow. Vernon leads machine learning, software engineering and data engineering teams who create automated offers and automated pricing services for underwriting and resale of residential real estate nationally for Zillow...
Read more
Track Host
Francesca Lazzeri
Principal Data Scientist Manager @Microsoft
Francesca Lazzeri, PhD is an experienced scientist and machine learning practitioner with over 12 years of both academic and industry experience. She is author of the book “Machine Learning for Time Series Forecasting with Python” (Wiley) and many other publications, including...
Read more