Ready, set, go: Using TensorFlow to prototype, train, and productionalize your models (sponsored by Google)
Building machine learning models is a multistage process. TensorFlow's high-level APIs make this process smooth and easy, whether you're starting small or going big. Karmel Allison walks you through a practical example of building, training, and debugging a model and then exporting it for serving using these APIs.
Talk Title | Ready, set, go: Using TensorFlow to prototype, train, and productionalize your models (sponsored by Google) |
Speakers | Karmel Allison (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 | |
Building machine learning models is a multistage process. TensorFlow’s high-level APIs make this process smooth and easy, whether you’re starting small or going big. Karmel Allison walks you through a practical example of building, training, and debugging a model and then exporting it for serving using these APIs. This session is sponsored by Google.