Thomas J. Fan – Scikit-learn on GPUs with Array API | PyData NYC 2023

The PyData conference in NYC 2023 will feature a keynote presentation by Thomas J. Fan on the topic of “Scikit-learn on GPUs with Array API”. This topic is generating a lot of excitement in the data science community, as it promises to revolutionize the way machine learning models are trained and deployed.

Thomas J. Fan is a renowned expert in the field of machine learning and has been actively involved in the development of Scikit-learn, a widely used machine learning library in Python. His work on optimizing Scikit-learn to run on GPUs with the Array API has the potential to greatly accelerate the training of machine learning models, making it possible to work with much larger datasets and more complex models.

During his keynote presentation at PyData NYC 2023, Thomas J. Fan will delve into the technical details of how Scikit-learn can be adapted to take advantage of GPU acceleration through the Array API. He will also discuss the potential impact of this development on the broader data science community, and how it can open up new possibilities for solving complex real-world problems.

This presentation is expected to attract a large audience of data scientists, machine learning engineers, and researchers who are eager to learn about the latest advancements in machine learning technology. Attendees will have the opportunity to gain valuable insights from Thomas J. Fan’s expertise and to network with other professionals in the field.

In addition to Thomas J. Fan’s keynote presentation, the PyData NYC 2023 conference will feature a wide range of talks, workshops, and networking events focused on data science and machine learning. This will be an invaluable opportunity for anyone working in these fields to stay up to date with the latest trends and developments, and to connect with peers and experts in the industry.

Overall, Thomas J. Fan’s presentation on “Scikit-learn on GPUs with Array API” is sure to be a highlight of the PyData NYC 2023 conference, and it is not to be missed by anyone with an interest in machine learning and data science. Be sure to mark your calendar and reserve your spot at this exciting event.