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Making a Basic Keras Model - Input Shape and Parameters
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Making a Basic Keras Model - Input Shape and Parameters
Hey Guys!

I am currently trying to build a simple model which I plan to use to make predictions. The idea for this model is to have each of the 202-dimensional vectors in an array (300 in total) be fitted (using to a 1 dimensional vector containing a single integer (also 300 in total). Currently, I have two numpy arrays with the following dimensions: [300,202] and [300,]. I am really having difficulty constructing this model. Here is the current code that I have:

model = tf.keras.Sequential()

model.add(tf.keras.layers.Dense(128, activation="relu"))

model.compile(loss = "mean_squared_error", optimizer=tf.keras.optimizers.Adam(0.1))

#"states" has shape [300,202] and "actions" has shape[300,]

history =, actions, epochs = 1, verbose=False)

Here is the error message that I keep getting:
"ValueError: Error when checking input: expected input_1 to have shape (202,) but got array with shape (1,)"
Any help that you guys could provide would be great! I'd be more than happy to clarify anything!

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