Artificial intelligence is the single most transformative tool used across industries today. At this year’s MWC Los Angeles, the Global System for Mobile Communications (GSMC) has partnered with the NVIDIA Deep Learning Institute (DLI) to offer hands-on, self-paced training on intelligent video analytics, signal processing, data science, and more, powered by GPUs in the cloud.
Plug into industry expertise. Charge up your AI skills.
The Deep Learning Institute has trained developers, researchers and data scientists around the world. Now, all conference attendees will have the chance to participate in hands-on, self-paced courses alongside their peers, with access to experts.
Trainings are on a first come first serve basis. Come find the Deep Learning Institute in the South Hall, Booth 1753. Experts will be on hand to answer any questions and laptops will be provided.
Understand how to refactor existing CPU-only data science workloads to run much faster on GPUs and write accelerated data science workflows from scratch. The open-source RAPIDS project allows data scientists to GPU-accelerate their data science and data analytics applications end-to-end, creating possibilities for drastic performance gains and techniques not available through traditional CPU-only workflows.
Use Horovod to effectively scale deep learning training in new or existing code bases. Scale deep learning training to multiple GPUs with Horovod, the open-source distributed training framework originally built by Uber and hosted by the LF AI Foundation.
Learn how to classify both image and image-like data using deep learning by converting radio frequency (RF) signals into images to detect a weak signal corrupted by noise. Deep neural networks are better at classifying images than humans, which has implications beyond what we expect of computer vision.
Learn how to utilize TF-TRT to achieve deployment-ready optimized models. Generate high-performance deep learning models in the TensorFlow platform using a built-in TensorRT library (TF-TRT) and Python.
Explore how to create AI-based video analytics applications using DeepStream to transform video streams into actionable insights. The DeepStream framework features hardware-accelerated building blocks of intelligent video analytics (IVA) applications, allowing developers to focus on building core deep learning networks.