Input 0 of layer sequential is incompatible with the layer: expected shape=(None, 8), found shape=(None, 16)

#fix for: Primary TermInput 0 of layer "sequential" is incompatible with the layer: expected shape=(None, 8), found shape=(None, 16)

#The Tensorflow model expects the first dimension of the input to be the batch size, 
#in the model declaration however they set the input shape to be the same shape as the input. 

#To fix this you can change the input shape of the model to be the number of feature in the dataset.

model.add(tf.keras.layers.Dense(256, input_shape=(x_train.shape[1],), activation='sigmoid'))
#The number of rows in the .csv files will be the number of samples in your dataset. Since you're not using batches, the model will evaluate the whole dataset at once every epoch