PyTorch is a recent deep learning framework from Facebook that is gaining massive momentum in the deep learning community. Its fundamentally flexible design makes building and debugging models straightforward, simple, and fun. Delip Rao and Brian McMahan walk you through PyTorch’s capabilities and demonstrate how to use PyTorch to build deep learning models and apply them to real-world problems. Join in to learn how to input a range of data and variables into your models—from text to images and beyond—and rapidly prototype and construct solutions for a range of common machine learning tasks.
Delip Rao is the founder of R7 Speech Science, a San Francisco-based company focused on building innovative products on spoken conversations. Previously, Delip was the founder of Joostware, which specialized in consulting and building IP in natural language processing and deep learning. Delip is a well-cited researcher in natural language processing and machine learning and has worked at Google Research, Twitter, and Amazon (Echo) on various NLP problems. He is interested in building cost-effective, state-of-the-art AI solutions that scale well. Delip has an upcoming book on NLP and deep learning from O’Reilly.
Brian McMahan is a research engineer at Joostware, a San Francisco-based company specialized in consulting and building intellectual property in natural language processing and deep learning. He is also a cofounder at R7 Speech Sciences, a company focused on understanding spoken conversations. Brian is wrapping up his PhD in computer science from Rutgers University, where his research focuses on Bayesian and deep learning models for grounding perceptual language in the visual domain. Brian has also conducted research in reinforcement learning and various aspects of dialogue systems.
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