I want to split my full dataset(every raw data has multiple features) into train and test sets. Rather than using scikit-learn 's train-test-split is there any other proper way to split my data? as well as I need to shuffle my data when splitting. (If the suggested method is based on tensorflow, it's too better.)
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Try this code:
import tensorflow as tf
input = tf.random.uniform([100, 5], 0, 10, dtype=tf.int32)
input = tf.random.shuffle(input)
train_ds = input[:90]
test_ds = input[-10:]

Andrey
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