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## Environment info
* Operating System: Windows 8.1 / 10, Windows Server 2012 / 2016, WSL Ubuntu 16.04, Clear Linux (latest)
* CPU: Quad Intel Xeon 6154, 768GB RAM (72 physical cores, all 3.7 GHz,…
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Once we have decided on the specifics of our model, we need to do two processes: Compile the model and fit the data to the model.
We can compile the model like so:
`model.compile(optimizer='sgd', l…
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Once we have decided on the specifics of our model, we need to do two processes: Compile the model and fit the data to the model.
We can compile the model like so:
`model.compile(optimizer='sgd', l…
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### System information
- OS Platform and Distribution: Linux Ubuntu 18.04.5 LTS (Bionic Beaver)
- TensorFlow installed from: Conda
- TensorFlow version: 2.2.0
- Python version: 3.6.9
- CUDA/cuDNN…
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Once we have decided on the specifics of our model, we need to do two processes: Compile the model and fit the data to the model.
We can compile the model like so:
`model.compile(optimizer='sgd', l…
-
Once we have decided on the specifics of our model, we need to do two processes: Compile the model and fit the data to the model.
We can compile the model like so:
`model.compile(optimizer='sgd', l…
-
Once we have decided on the specifics of our model, we need to do two processes: Compile the model and fit the data to the model.
We can compile the model like so:
`model.compile(optimizer='sgd', l…
-
Once we have decided on the specifics of our model, we need to do two processes: Compile the model and fit the data to the model.
We can compile the model like so:
`model.compile(optimizer='sgd', l…
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**Describe the bug**
At the end of an optimization with the neural net learner, the predicted cross sections show signs of overfitting. I haven't done a full study on how this affects optimizations, …
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Once we have decided on the specifics of our model, we need to do two processes: Compile the model and fit the data to the model.
We can compile the model like so:
`model.compile(optimizer='sgd', l…