The hottest topics in computer science today are machine learning and deep neural networks. Many problems deemed “impossible” only five years ago have now been solved by deep learning, including playing Go, recognizing what is in an image, and translating languages. Software engineers are eager to adopt these new technologies as soon as they come out of research labs. Join in to learn how to do so.
Martin Görner explores the newest developments in image recognition and convolutional neural network architectures and shares tips, engineering best practices, and pointers to apply these techniques in your projects. No PhD required.
This session is sponsored by Google.
Martin Görner works in developer relations at Google, where he focuses on parallel processing and machine learning. Passionate about science, technology, coding, algorithms, and everything in between, Martin’s first role was in the Computer Architecture Group at STMicroelectronics. He also spent 11 years shaping the nascent ebook market, starting at Mobipocket, which later became the software part of the Amazon Kindle and its mobile variants. He holds a degree from Mines Paris Tech.
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