Accelerated Python on GPUs

 

Python, pandas, scikit-learn are essential tools for any Data Scientist today. They are user friendly and rely on the popular Python syntax that is easy to read and implement for Data Science work. However, any Data Scientist who has used them knows that the limits they have are real when it comes to being able to load large datasets or the amount of time it takes to train a model. This is because of the limitations that come with CPU computing. RAPIDS is a suite of Python packages that allows Data Scientists to take advantage of GPUs in their normal workflow. By implementing simple, syntactical changes, Data Scientists can work with significantly larger Dataframes in-memory and run model training and inference in a fraction of the time they could with CPU based Python. By taking advantage of RAPIDS, a Data Scientist can process larger datasets and in less time than they could otherwise. This saves time and money. And one can take advantage of RAPIDS wherever they like: on their computer, in the cloud (AWS, Google Cloud or Azure) or on-prem servers. The possibilities are endless!

Agenda:

11:50 am - 12:00 pm Arrival and socializing

12:00 pm - 12:10 pm Opening

12:10 pm - 1:50 pm Subhan Ali, " Accelerated Python on GPUs"

1:50 pm - 2:00 pm Q&A

Speaker: Subhan Ali, NVIDIA

Zoom link

Webinar ID: 818 4951 4640