Machine learning task [closed]
Closed 1 hour ago.
Machine learning task [closed]
Closed 1 hour ago.
Machine learning task [closed]
Closed 1 hour ago.
Machine learning task [closed]
Closed 1 hour ago.
Machine learning task [closed]
Closed 1 hour ago.
Machine learning task [closed]
Closed 1 hour ago.
How to Improve Machine Learning on Basic Data Set?
I am trying to learn machine language using Python and the TensorFlow module. I am not having much success getting accurate predictions. My apologies, as I’m not a trained coder or data scientist. As shown in my code below, I’m providing a very simple data set, one that should be perfectly predictable to even an 8-year old, but my machine learning models (sequential network/LSTM and dense neural network) don’t work very well. To be clear, the data set is X = y = numbers from 10 to 800, stepping by 10 (so 10, 20, 30, …, 800). The prediction for y at time n+1 should simply be X + 10 at time n. So if X = 500, we predict y (at next point n) will = 510.
why is my code outputting “audio_features is empty. Skipping LSTM preparation.”
I’m trying to import a librispeech
dataset into my code and then train using it but I keep getting:
why is my code outputting “audio_features is empty. Skipping LSTM preparation.”
I’m trying to import a librispeech
dataset into my code and then train using it but I keep getting:
why is my code outputting “audio_features is empty. Skipping LSTM preparation.”
I’m trying to import a librispeech
dataset into my code and then train using it but I keep getting: