Keras AttributeError: 'list' object has no attribute 'ndim'

I don't know the shape of your training data but I suspect that you have an error on your input_dim. Try changing it to input_dim=len(X_data) like this:

model  = Sequential()
model.add(Dense(5, input_dim=len(X_data), activation='sigmoid' ))
model.add(Dense(1, activation = 'sigmoid'))
model.compile(loss='mean_squared_error', optimizer='adam', metrics=['acc']), y_data, epochs=20, batch_size=10) expects x and y to be numpy array. Seems like you pass a list, it tried to get shape of input by reading ndim attribute of numpy array and failed.

You can simply transform it using np.array:

import numpy as np
...,np.array(train_Y), epochs=20, batch_size=10)

When you import you should use tensorflow.keras instead of just keras like this:

from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Input, Conv2D, MaxPool2D, Dense

because there is a bug related to the keras module.

Reference: here.