Open House: Designing Efficient Deep Learning Systems
The stakes are high when implementing deep learning. Whether in computer vision, speech recognition, or robotics, deep learning requires efficient hardware systems to operate optimally and at scale. Engineers can get lost in the computational complexity of deep learning, so confidence in the foundations and trends of deep learning are essential to deploying the technology effectively across an organization.
Designing Efficient Deep Learning Systems, a two-day on-campus course led by MIT associate professor Vivienne Sze, will teach engineers and developers how to design and build deep learning systems. Starting from the foundations and moving into trends in efficient processing techniques, participants will leave with a better understanding of various deep learning architectures and be able to evaluate which custom hardware is most relevant to their organization.
At this virtual open house, you will:
- Meet Vivienne Sze, an electrical engineering and computer science associate professor at MIT
- Review the learning outcomes and instruction method that includes demonstrations, lectures, and group work
- See how this course will advance your current knowledge of deep learning and impart the practical skills to adopt the right architecture for your deep learning systems
- Ask your course questions during a live Q&A session