Detect and Remove Outliers from Pandas DataFrame
Z-score re-scale and center(Normalize) the data and look for data points which are too far from zero(center). Data points far from zero will be treated as the outliers. In most of the cases, a threshold of 3 or -3 is used i.e if the Z-score value is greater than or less than 3 or -3 respectively, that data point will be identified as outliers.
How to normalize, mean subtraction, standard deviation, zero center image dataset in Python?
standardize the inputs to your network as much as possible, so that learning is more stable by reducing variability across the training data. In terms of normalization of the data, that all features are in the same range so that they contribute equally.
Keras Custom Training Loop
You can do this whether you’re building Sequential models, Functional API models, or subclassed models. Using this custom training algorithm, you still get the benefit from the convenient features of fit(), such as callbacks, built-in distribution support, or step