Attend live events in the time zone that works best for you, or browse an extensive catalog of on-demand content showcasing innovative uses of GPU technology.
Overview
The GTC Data Science Presentations conference, taking place from October 5-9, will feature advancements in data science and GPU technologies. Attendees can participate in live events or access a catalog of on-demand content focused on innovative data science applications.
What You'll Learn
1
How to write estimators that can scale from single-core to distributed cores on NVIDIA GPUs
2
How to generate ensemble-based adversarial attacks for online fraud detection
3
How to use RAPIDS Accelerator for Apache Spark to improve Spark workloads
Key Questions Answered
What are the main topics covered in the GTC Data Science Presentations?
The GTC Data Science Presentations will cover topics such as scalable custom machine learning estimators, ensemble-based adversarial attacks for fraud detection, and the use of NVIDIA GPUs with Google Cloud Dataproc to enhance Spark workloads. These sessions aim to showcase innovative applications of data science technology.
When is the GTC Data Science conference taking place?
The GTC Data Science conference will take place from October 5 to October 9, running continuously across seven time zones. This format allows participants to attend live events or access on-demand content at their convenience.
How does the RAPIDS Accelerator for Apache Spark improve performance?
The RAPIDS Accelerator for Apache Spark enhances performance by leveraging columnar data processing to accelerate ETL processing without requiring changes to the user's query code. This integration with NVIDIA GPUs helps improve latency and reduce costs for select Spark workloads.
Technologies & Tools
Hardware
Nvidia Gpus
Used for scalable custom machine learning estimators and enhancing Spark workloads.
Cloud Service
Google Cloud Dataproc
Supports Spark workloads using RAPIDS Accelerator to improve latency and reduce costs.
Software
Rapids Accelerator For Apache Spark
An open-source plugin that accelerates ETL processing without changes to user query code.
Key Actionable Insights
1Attending the GTC Data Science Presentations can provide insights into cutting-edge advancements in data science and GPU technologies.This conference is an excellent opportunity for software engineers to learn about innovative applications and best practices in the field, which can enhance their skill set and project outcomes.
2Utilizing the RAPIDS Accelerator for Apache Spark can significantly improve the performance of data processing tasks.By adopting this technology, teams can achieve faster ETL processing and better resource management, ultimately leading to cost savings and improved efficiency in data workflows.
3Understanding ensemble-based adversarial attacks is crucial for developing robust online fraud detection systems.As fraud detection becomes increasingly sophisticated, leveraging advanced techniques like ensemble-based attacks can help organizations stay ahead of potential threats and improve their security measures.