When running the 5th notebook "Linear Model and Neural Network From Scratch", there is a type error when trying to convert the dataframe to a tensor.
This code gives the error:
indep_cols = ['Age', 'SibSp', 'Parch', 'LogFare'] + added_cols
t_indep = tensor(df[indep_cols].values, dtype=torch.float)
t_indep
The error: TypeError: can't convert np.ndarray of type numpy.object_. The only supported types are: float64, float32, float16, complex64, complex128, int64, int32, int16, int8, uint8, and bool.
I was able to get around the error by converting the values into a list, but that threw a warning that that method was very slow and to try using an np array. Changing the code to use a np array gives the original error so that didn't help.
What is the best way to do the conversion?
When running the 5th notebook "Linear Model and Neural Network From Scratch", there is a type error when trying to convert the dataframe to a tensor.
This code gives the error:
The error: TypeError: can't convert np.ndarray of type numpy.object_. The only supported types are: float64, float32, float16, complex64, complex128, int64, int32, int16, int8, uint8, and bool.
I was able to get around the error by converting the values into a list, but that threw a warning that that method was very slow and to try using an np array. Changing the code to use a np array gives the original error so that didn't help.
What is the best way to do the conversion?