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In the validation/before/inputs.md, say we do not typically take into account and "imbalance in nature", but rather have uniform/balanced classes when training. Practically, this means a balance between signal and background, different HT bins, or any other group of classes.
Add more example code throughout. In most sections, this simply means showing an example of the relevant TensorFlow/PyTorch/ONNX code.
Add back in the links for validation/before/domains.md, which needs something like, "Last but not the least, a usage of bayesian neural networks has a great advantage..." The problem is that the Bayesian neural network PR hasn't been merged in yet and it's causing the webpage building to fail.
validation/before/inputs.md) to thevalidation/throughout/overfitting.mdsectionvalidation/before/inputs.md, say we do not typically take into account and "imbalance in nature", but rather have uniform/balanced classes when training. Practically, this means a balance between signal and background, different HT bins, or any other group of classes.validation/before/domains.md, which needs something like, "Last but not the least, a usage of bayesian neural networks has a great advantage..." The problem is that the Bayesian neural network PR hasn't been merged in yet and it's causing the webpage building to fail.