knowledge Transfer

Using the correlation coefficient you can find out how these two variables are related and to what degree. Please note that this is only a part of the whole dataset.

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.

Many machine learning models are designed with the assumption that each feature values close to zero or all features vary on comparable scales. The gradient-based model assumes standardized data.

AlertDialog has the ability to display different kinds of widgets. Here we will see the 3 different types of ListView to display the list in AlertDialog and how to set dialog width and height to fit actual items size.

RaggedTensor is a new type of Tensor, it efficiently represents sequence data. It designed to handle text and other variable-length sequences. It native representation of sequences of varying shapes.

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.

Leaky ReLU function is nearly identical to the standard ReLU function. The Leaky ReLU sacrifices hard-zero sparsity for a gradient which is potentially more robust during optimization. Alpha is a fixed parameter(float >= 0.).

sample_weights functionality adds more importance to some samples than others during training.so that the loss function used by the model is weighted per-sample not per class. It changes the way the loss is calculated

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

Every FormField has it’s own validate function and within that validate function it will invoke the validator. The error message is displayed in the TextField.