TensorFlow, deep learning, and modern convolutional neural nets, without a PhD (sponsored by Google)
Martin Grner 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.
Talk Title | TensorFlow, deep learning, and modern convolutional neural nets, without a PhD (sponsored by Google) |
Speakers | Martin Görner (Google) |
Conference | Artificial Intelligence Conference |
Conf Tag | Put AI to Work |
Location | San Francisco, California |
Date | September 5-7, 2018 |
URL | Talk Page |
Slides | Talk Slides |
Video | |
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.