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View Code? Open in Web Editor NEWTensorFlow and Scikit Flow examples
License: Apache License 2.0
TensorFlow and Scikit Flow examples
License: Apache License 2.0
Hello, I'm unable to run this example with tensor flow 9.
Here is my bug reports on tensorflow issue tracker :
hello
v I'm unable to run this example using spyder(python3.5)
https://gist.githubusercontent.com/ilblackdragon/e956a9da159aade0c893467e49afd057/raw/c1d61db5c748e007923d3fae2fbb85e7593a9087/titanic_all_features.py
here is the error
TypeError: unorderable types: int() < str()
any suggestion please?
Hello, thanks for sharing the code.
Originally, sequence-to-sequence is for language transformation. Can it be used for transforming(mapping) a numerical sequence to another numerical sequence. With respect to numerical sequence, each component of which is itself a floating value, e.g., 0.006, or 201.25, etc. In other words, can seq-to-seq be used to solve the problem such as [0.002, 0.1, 0, 100, 201] --> [-0.02, 0.3, 20]. Thanks.
i do not understand why do you so ?
Can you add an example with using both continuous data (e.g., age and fare) and categorical data (e.g., class) as input for the tensorflow neural network implementation? I have been struggling with specifically how to set up "feature_columns" for it.
AttributeError: module 'tensorflow.contrib.learn' has no attribute 'infer_real_valued_columns_from_input'
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