`tf.distribute.Strategy` is integrated to `tf.keras`, so when `model.fit` is used with `tf.distribute.Strategy` instance and then using `strategy.scope()` for your model allows to create distributed variables. #TensorFlow#DataScience#DeepLearning
7/n This allows it to equally divide your input data on your devices.
You can use `tf.distribute.Strategy` with very few changes to your code, because the underlying components of TensorFlow have been changed to become strategy-aware.
3/ If the p-value from the test is less than some significance level (e.g. α = .05), then we can reject the null hypothesis and conclude that the time series is stationary.
2/ It is important to standardize variables before running Cluster Analysis. It is because cluster analysis techniques depend on the concept of measuring the distance between the different observations we're trying to cluster.
"roc_auc_score" is defined as the area under the ROC curve, which is the curve having False Positive Rate on the x-axis and True Positive Rate on the y-axis at all classification thresholds.