Training State-of-the-Art Neural Networks in the Microsoft Azure Cloud
This is the third post in a three-part series by guest blogger, Adrian Rosebrock. Adrian writes at PyImageSearch.com about computer vision and deep learning using Python. He recently finished authoring a new book on deep learning for computer vision and image recognition.
Introduction In the final part in this series, I want to address a question I received from Mason, a PyImageSearch reader, soon after I published the first post in the series:
Adrian, I noticed that you said tested all of the code for your new deep learning book on the Microsoft Data Science Virtual Machine (DSVM). Does that include the chapters on training networks on the ImageNet dataset as well? I work at a university and we’re allocating our budget for both physical hardware in the lab and cloud-based GPU instances. Could you share your experience training large networks on the DSVM? Thanks. – Mason
Mason poses a great question – is it possible, or even advisable, to use cloud-based solutions such as the Microsoft DSVM to train state-of-the-art neural networks on large datasets?