Deep learning continues to push the state of the art in domains such as computer vision, natural language understanding, and recommendation engines. One of the key reasons for this progress is the availability of highly flexible and developer-friendly deep learning frameworks. Joseph Spisak and Sunil Mallya offer an introduction to the powerful and scalable deep learning framework Apache MXNet. You’ll gain hands-on experience using MXNet with preconfigured Deep Learning AMIs and CloudFormation Templates to help speed your development and quickly spin up AWS GPU clusters to train at record speeds. You’ll also learn how to leverage the NVIDIA DLI as you walk through the mechanics of using MXNet and explore several end-to-end application examples that apply deep learning to event prediction, language modeling, and computer vision.
Joseph Spisak manages deep learning product management at AWS. Joseph has experience driving strategies and technical and business engagements around machine learning-based cloud workloads, such as computer vision, natural language processing, video summarization and analysis, and speech recognition. Joseph has more than 15 years’ experience delivering products and services in digital video, cloud-based media transcoding, image processing, and machine and deep learning in the consumer mobile, broadcast, and cloud segments. Joseph holds a bachelor’s degree in electrical engineering from Michigan State University and an MBA and MS in finance from the University of Denver. He is a proud graduate of the Entrepreneurial and Innovation certificate program at Stanford University’s Graduate School of Business.
Sunil Mallya is a solutions architect focused on deep learning at AWS, where he works with customers in various industry verticals. Sunil has an acute passion for serverless computing. Previously, he cofounded the neuroscience- and machine learning-based image analysis and video thumbnail recommendation company Neon labs and worked on building large-scale low-latency systems at Zynga. He hold a master’s degree in computer science from Brown University.
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