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The plan for TensorFlow 2.0: delightfully productive, user-friendly workflows across a broad range of use cases, from cutting-edge research to applications development and deployment. It will no longer be a "framework", it will be an ecosystem of solutions that all work together.
In particular, it's clear to me that the same model-building API style cannot work for all users. Researchers & hackers have fundamentally different needs, constraints, and tolerance for complexity than data scientists. The key is to provide a coherent spectrum of solutions.
It’ll be awesome if it becomes easier to deploy models in AWS Lambda or Google Cloud Functions.
Looking forward to it
You'll update your book on it?
Including deployment will make TF very useful. Making library of how-to’s and technical solutions to common problems could lower the entrance barrier.
Eagerly waiting for TF 2.0 and @aureliengeron 's updated book in April. Right now, i am learning from http://fast.ai and will start Abu mostafa's Caltech course soon. Preferring Abu's course over Andrew's as it isn't watered down.
Testing and interpretability should become the biggest priority. Especially stuff like Lime, etc.
What about small and lightweight C++ libraries for embedded devices?
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