TensorFlow and deep learning (without a PhD)
With TensorFlow, deep machine learning has transitioned from an area of research into mainstream software engineering. Martin Grner walks you through building and training a neural network that recognizes handwritten digits with >99% accuracy using Python and TensorFlow.
Talk Title | TensorFlow and deep learning (without a PhD) |
Speakers | Martin Görner (Google) |
Conference | Strata Data Conference |
Conf Tag | Making Data Work |
Location | London, United Kingdom |
Date | May 23-25, 2017 |
URL | Talk Page |
Slides | Talk Slides |
Video | |
With TensorFlow, deep machine learning has transitioned from an area of research into mainstream software engineering. Martin Görner walks you through building and training a neural network that recognizes handwritten digits with >99% accuracy using Python and TensorFlow. Along the way, Martin discusses many standard deep learning techniques such as minibatching, learning rate decay, dropout, convolutional networks, and more and demonstrates how to implement them in TensorFlow.