i have a tensorflow dataset that contains several elemets:
string, int & bool
for element in train_df.take(1):
print(element)
(OrderedDict([('textfield', <tf.Tensor: shape=(1,), dtype=string, numpy=array([b'240300'], dtype=object)>), ('boolfield', <tf.Tensor: shape=(1,), dtype=bool, numpy=array([ True])>), ('intfield', <tf.Tensor: shape=(1,), dtype=int64, numpy=array([1853])>)]), <tf.Tensor: shape=(1,), dtype=int64, numpy=array([1])>)
i wonder how i can convert them before training to numeric values.
i've saw that are several techniques like:
- layer transformation
- dataset transformation
- tfx
but im not sure how to do it and when to use each of them
can you assist please?
question from:
https://stackoverflow.com/questions/65831901/tensorflow-dataset-string-bool-transformation-for-both-bool-string-values-how 与恶龙缠斗过久,自身亦成为恶龙;凝视深渊过久,深渊将回以凝视…