RAPIDSFire RAPIDS
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Follow the RAPIDSFire podcast for a fresh take on data science. Hear from revolutionaries transforming data science on GPUs for scientific research, higher education, and the broader enterprise. Talks with open-source software maintainers, Kaggle grandmasters, practitioners, CUDA experts and many others keep you up-to-date on the most exciting developments. Let's discuss how to make your work better and faster. Hosted by Data Scientist Paul Mahler.
Join the conversation and send feedback on Twitter @rapidsai
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RAPIDSFire Sports Spectacular 1 - Sam Moss and Cameron Weinert of Every Day is Saturday
I talk with Sam Moss and Cameron Weinert about using data science to predict college football. We talk about feature engineering, following your passing, the role of analytics in sports and sports fandom, how to be an intelligent consumer of data science as a non-data scientist, and a lot more.
Everyday is Saturday on Spotify.
Everyday is Saturday on Apple.
Sam on Twitter.
Raw data on college football here at collegefootballdata.com -
Marlene Mhangami on Python, Pivots, and Personal Growth (and RAPIDS on Windows)
We talk with Marlene Mhangami, a director and chair of the Python Software Foundation, co-founder of coding education non-profit ZimboPy, someone that took a huge career pivot from pre-med to software engineering, and one of the folks that helped bring RAPIDS to Windows. We talk about changing careers, creativity and confidence in tech, and of course RAPIDS on Windows.
Marlene's home page
https://marlenemhangami.com/
Marlene's blog post about RAPIDS on Windows
https://medium.com/rapids-ai/running-rapids-on-microsoft-windows-10-using-wsl-2-the-windows-subsystem-for-linux-c5cbb2c56e04
Tutorial on using RAPIDS on Windows via WSL2
https://www.youtube.com/watch?v=jnEd3IDsF-I
ZimboPy on github
https://github.com/ZimboPy -
Even Oldridge on Tabular Deep Learning and the Future of Recommender Systems
This week we’re joined by Even Oldridge, Senior Manager, RecSys Platform Team at NVIDIA. We talk about Tabular Deep Learning, NVMerlin, how bookstores aren’t like recommender systems, his team’s recent repeat win in the ACM Recsys Challenge, the future of recommender systems and more.
NVIDIA Merlin on the NVIDIA Developer Blog
https://developer.nvidia.com/blog/tag/merlin/
NVIDIA Merlin blogs on Medium
https://medium.com/nvidia-merlin
Merlin on Github
https://github.com/NVIDIA-Merlin/Merlin
NVTabular Blogs
https://developer.nvidia.com/blog/tag/nvtabular/
NVTabular on Github
https://github.com/NVIDIA/NVTabular
REES46 data set mentioned toward the end of the podcast
https://rees46.com/en/datasets -
Way of the Grandmaster 2 with Christof Henkel
We talk with 4-time Kaggle winner Christof Henkel about how he got started in Kaggle, important skills for Kaggle success, his most memorable contests, his most recent victory, how an alien radio signal is like a bird call, climbing at the 2021 Olympics, and much more!
Christof's Kaggle Profile: https://www.kaggle.com/christofhenkel
Christof's Twitter: https://twitter.com/kagglingdieter -
Way of the Grandmaster with Chris Deotte
We sit down and talk with 4x Kaggle Grandmaster Chris Deotte about his career, how he got started doing Kaggle, how you can get started doing Kaggle, feature engineering, the perks of AGI, and a lot more!
Chris on Kaggle: https://www.kaggle.com/cdeotte -
Data Science, Social Science, and the Near Future of RAPIDS with John Zedlewski
I sit down and talk with the new Director of Engineering for RAPIDS at NVIDIA, John Zedlewski about what economics can learn from machine learning practitioners, engineering challenges that ended up being harder than first thought, how increased automation will change the day-to-day work of data scientists, and much more.