A GPU is one of the most important components of modern-day artificial intelligence and deep learning architecture. Enterprises and developers are constantly on the lookout for tools that help them build and manage end-to-end data science and analytics pipelines seamlessly. RAPIDS is one such a tool incubated by NVIDIA® based on the company’s expert experience in hardware and data science.
RAPIDS uses NVIDIA CUDA® primitives for low-level compute optimisation, and lets developers use GPU parallelism and high-bandwidth memory speed through user-friendly Python interfaces.
RAPIDS’s also helps with data preparation tasks for data science pipelines. With support for multi-node and multi-GPU deployments, RAPIDS is fast becoming a favourite among deep learning and data science developers.
With this in mind, NVIDIA and Analytics India Magazine are arranging a day-long workshop which will help developers and data scientists to fully leverage and improve their data science pipeline using RAPIDS.
RAPIDS also includes projects like cuDF, a powerful data manipulation library; cuML, a collection of machine learning libraries; and cuGraph, an efficient and accelerated graph analytics library. The projects are well maintained with highly-efficient communities.
Analytics India Magazine will be teaming up with NVIDIA to bring to engineers and data scientists a workshop focused on techniques such as RAPIDS, Data ETL Pipeline and algorithms. Attendees will be able to learn how to use RAPIDS and have hands-on experience with data ETL pipelines.
Titled ‘NVIDIA RAPIDS GPU-Accelerated Data Analytics & Machine Learning Workshop’ the workshop will offer industry insights on how to make your data science pipelines better. The workshop will include a keynote conducted by:
Sundara Ramalingam Nagalingam – Head Deep Learning Practice, NVIDIA
Mitra Rath – Senior Solution Architect, NVIDIA
The workshop will take the participants through the following topics:
- Current Challenges in Machine learning and data science
- RAPIDS Technical Overview and Software Architecture
- Hand-on Session Covering RAPIDS end-to-end data science workflow
Who Should Attend?
- Data Engineers and Data Scientists looking to supercharge their training and inference workflows.
- Data Science managers looking for an upgrade to existing infrastructure.
- AI/ML enthusiasts with experience in basic concepts of ML, data science, workflows and have worked with Python, Scikit-learn, or Pandas.
Time: 9 AM
Venue: L-6, 8th Floor, NVIDIA, Manyata Tech Park, Nagawara, Bengaluru
Date: 18 October 2019