Reflections on AnacondaCON 2019 with NVIDIA's Josh Patterson
Apr 30, 2019By Anaconda Team
I love this month. April 19’ brings back Game of Thrones, Avengers: Endgame (that Thanos snap though), and of course AnacondaCON. I’ve been to every AnacondaCON, which makes this my third show. Of all data science conferences on my circuit, AnacondaCON is a show that I’ll never miss because it’s the perfect balance of technology, community, and honest conversations questioning “how do we get better”. AnacondaCON is:
- A community centric conference where you practically know or have the opportunity to meet most everyone;
- exceptional technical content focused on data science, delivery, and open source Python development;
- a solid mix of enterprise customers and partners desires; and
- Austin in the spring! Great food and weather (except the rain this year).
This was the first AnacondaCON for RAPIDS. For those who don’t know, RAPIDS is an open source data science platform incubated by NVIDIA® and based on years of accelerated data science experience. Simply put, our goal is to build a ridiculously fast and highly functional data science stack for practitioners to explore data, train machine learning algorithms, and build applications with NVIDIA GPUs.
We presented three core talks at that show covering multiple aspects of RAPIDS, including our CI stack, open source integration, and the RAPIDS roadmap for what’s coming next. We also demoed one of our many Jupyter notebooks showcasing GPU speed-ups on workflows. These notebooks are one of the best ways to get started experimenting, testing, and getting familiar with the platform.
The project is only six months young, but we’re moving quickly. We recently released RAPIDS 0.6 with tons of new functionality, improved documentation, new libraries, and much more. I invite you to come learn how you can leverage RAPIDS in your data science workflows. It’s open source. It’s really fast. But more importantly, it’s focused on you the community.
Be a part of the movement to accelerate your data science work. Join the RAPIDS community today. Let us know what you like, file issues on things that are not so lovely, and feel free to contribute on Github.