I have trained a two-stage ML model training for binary classification. In the first stage, I applied an autoencoder model consisting of encoder and decoder. The encoder model has reduced the dimension of the input feature from 1000 to 32. The decoder reconstructs the input by increasing the input feature from 32 to 1000. From the encoder output, I have applied a DNN model to binary classify whether the object is a flower or fruit.