Tuesday, April 6, 2:00 PM EST
By In this webinar, we’ll uncover how Saturn Cloud and Amazon Web Services provide flexible and easy solutions to data science infrastructure woes when it comes to compute resources, collaborative workspaces, and end-to-end tools for teams.
Tuesday, February 23, 2:00 PM EST
By Join our upcoming workshop to learn best practices for faster, better performance on transfer learning and deep learning modeling tasks, how to train a computer vision model on a multi-machine GPU cluster using PyTorch, and more.
Wednesday, January 27, 1:00 PM EST
By In this workshop, attendees will get an introduction to LightGBM, a popular lightweight gradient-boosted decision tree (GBDT) library. This introduction will cover GBDTs generally and LightGBM, specifically. It will also describe which parts of a GBDT can be parallelized and how GBDT training works with multiple machines.
Tuesday, January 19, 3:00 PM EST
By In this hands-on workshop, attendees will have the opportunity to see how image classification tasks in PyTorch can be easily parallelized using Dask clusters on Saturn Cloud.
Wednesday, January 13, 2:00 PM EST
By In this webinar, we will introduce how data scientists can utilize Snowflake and Saturn Cloud together for their machine learning workloads and more.
Friday, December 18, 2:00 PM EST
By In this hands-on workshop, attendees will be introduced to Dask, a Python-native parallel computing framework. Dask extends traditional Python tools to operate at scale across a cluster of machines, removing memory and compute limitations. Instructors will walk step-by-step through setting up a Dask cluster, processing large datasets efficiently, and performing machine learning model training across the cluster.
Thursday, December 10, 2:00 PM EST
By In this hands-on workshop, attendees will learn how Dask and parallelization can be incorporated into standard PyTorch workflows to create faster inference and training, as well as higher quality training results. Instructors will walk step-by-step through how to run two types of computer vision jobs on GPU Dask clusters: large batch inference and transfer learning.
Wednesday, December 9, 1:30 PM EST
By Join us for an interactive discussion with Aaron Richter, Senior Data Scientist at Saturn Cloud, and Mike McCarty, Director of Software Engineering at Capital One. We will be discussing all things XGBoost along with packages, methods, tips for accelerating XGBoost performance in Python, and more.
Tuesday, November 10, 1:00 PM EST
By In this hands-on workshop, you’ll have the opportunity to see how a standard data science and machine learning workflow, using pandas and scikit-learn, can easily be parallelized using Dask clusters. Instructors will walk step-by-step through how to migrate existing Python code to Dask, an open-source framework enabling parallelization of Python.
Friday, October 30th, 1:30 PM EST
By Join Saturn Cloud’s Senior Data Scientist, Aaron Richter, and Travis Oliphant, CEO of OpenTeams and Quansight for an interactive discussion covering: The creation of NumPy and the start of the OSS PyData community and projects, how the data/AI ecosystem has changed over the last 10-20 years, Dask and Numba, how OSS tools will continue to be well-maintained moving forward, and more.
Thursday, October 29th, 10:30 AM PDT
By Data pipelines are crucial to an organization’s data science efforts. They ensure data is collected and organized in a timely and accurate manner, and is made available for analysis and modeling. In this talk, we’ll introduce the next-generation stack for big data pipelines built upon Prefect and Dask, and compare it to popular tools like Spark, Airflow, and the Hadoop ecosystem.
Tuesday, August 4, 2:00-3:00 PM EST
By Learn how to run up to 100x faster data science workloads in Python with Dask and RAPIDS and understand the infrastructure that’s necessary to launch high performance clusters and GPU machines in AWS.