Keras, how do I predict after I trained a model?

python theano deep-learning keras

model.predict() expects the first parameter to be a numpy array. You supply a list, which does not have the shape attribute a numpy array has.

Otherwise your code looks fine, except that you are doing nothing with the prediction. Make sure you store it in a variable, for example like this:

prediction = model.predict(np.array(tk.texts_to_sequences(text)))print(prediction)

python theano deep-learning keras

model.predict_classes(<numpy_array>)

python theano deep-learning keras

You must use the same Tokenizer you used to build your model!

Else this will give different vector to each word.

Then, I am using:

phrase = "not good"tokens = myTokenizer.texts_to_matrix([phrase])model.predict(np.array(tokens))

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