3) #TFX - Data Validation
— 👩💻 DynamicWebPaige @ #NeurIPS2018 🧠✨ (@DynamicWebPaige) November 22, 2018
How can you automatically ensure that the data being used to retrain your model is of the same format, source, naming conventions, etc., as the data that was used to train your model initially?
For online training, this is huge!https://t.co/fP0VLOwQeq pic.twitter.com/wewVeyRJbe
5) #TFX - Model Analysis
— 👩💻 DynamicWebPaige @ #NeurIPS2018 🧠✨ (@DynamicWebPaige) November 22, 2018
⚖️ My favorite use case for @TensorFlow Model Analysis is to check for any potential ethical issues in my model's input data or in its inferencing. You can interrogate data to ensure that no groups are being negatively impacted.https://t.co/MXMaCE1Wp8 pic.twitter.com/zkgQ4NUj0b
16) 🌱Seedbank
— 👩💻 DynamicWebPaige @ #NeurIPS2018 🧠✨ (@DynamicWebPaige) November 22, 2018
This also doesn't get talked about *nearly* enough.
Seedbank is an ever-expanding collection of interactive machine learning examples that you can use, modify, experiment with, and grow to meet your needs+use case. https://t.co/Gd0CRodKouhttps://t.co/LXx3y9Mg31
27) 🔍 Lucid
— 👩💻 DynamicWebPaige @ #NeurIPS2018 🧠✨ (@DynamicWebPaige) November 23, 2018
Interpretability—being able to explain why DNNs make the decisions they do—is *vital* for ethical machine learning and for the application of deep learning to high-consequence use cases.
📒 @GoogleColab tutorials, code, @distillpub articles: https://t.co/dLkXYYKWip pic.twitter.com/Q52GthPDE4
Great thread about TensorFlow. TensorFlow is not just a machine learning library, it's an ecosystem of APIs and products that covers an extremely wide range of use cases, from research and experimentation, to apps development, to production deployment. https://t.co/vJq7dcXfMZ
— François Chollet (@fchollet) November 26, 2018
