This two-day course is being offered in both instructor-led online and self-paced on-demand formats throughout the rest of the year, 2020. The course claims that, on completion, learners will be ready to apply GPU-accelerated deep learning techniques in MATLAB to common applications such as image classification, autonomous systems, voice recognition, and object detection.
MathWorks aims to provide a comprehensive platform for building AI-driven systems that are based on decades of supporting complex engineering projects. GPU Coder generates optimised CUDA code from MATLAB code for deep learning, embedded vision, and autonomous systems, which allows developers to build solutions that run efficiently on NVIDIA GPUs.
In addition, a MATLAB container from NVIDIA GPU Cloud (NGC), a hub for GPU-optimized AI and HPC software, provides a complete deep learning workflow that uses NVIDIA GPUs to accelerate neural network training to scale-up performance across nodes.
According to David Rich, the director of MATLAB marketing, MathWorks, “The NVIDIA Deep Learning Institute plays a crucial role in developing hands-on training and showcasing how to use new techniques like deep learning to solve complex problems.”
He further added, “This course offers a practical approach to deep learning that will help NVIDIA users to iterate quickly and converge on a solution that meets product and time-to-market requirements.”
“There’s been a surge of interest in the Deep Learning with MATLAB course using NVIDIA GPUs,” said Will Ramey, senior director and global head of developer programs at NVIDIA.
“Learning how to quickly and easily apply the power of NVIDIA GPUs to accelerate neural network training streamlines the process of application development and allows for more rapid deployment and faster time to market,” concluded Ramey.
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