I attempt to solve this problem 6 in this notebook. The question is to train a simple model on this data using 50, 100, 1000 and 5000 training samples by using the LogisticR
scikit-learn expects 2d num arrays for the training dataset for a fit function. The dataset you are passing in is a 3d array you need to reshape the array into a 2d.
nsamples, nx, ny = train_dataset.shape
d2_train_dataset = train_dataset.reshape((nsamples,nx*ny))
In LSTM, GRU, and TCN layers, the return_sequence in last layer before Dence Layer must set False . It is one of conditions that you encounter to this error message .