>> Figure-2 shows that performance of deep learning is much better than non-deep learning algorithm.
This is a nonsensical over-generalization.
>> In addition, it is automatically do the feature extraction.
At the cost of interpretability. Let's not even mention the dreadful nights of tweaking parameters (such as dropout probability, activation function, network architecture, learning rate, optimization function, various pre-processing tricks, pre-training to warm-start, convolution parameters, maxpool parameters, and so much more).
This is a nonsensical over-generalization.
>> In addition, it is automatically do the feature extraction.
At the cost of interpretability. Let's not even mention the dreadful nights of tweaking parameters (such as dropout probability, activation function, network architecture, learning rate, optimization function, various pre-processing tricks, pre-training to warm-start, convolution parameters, maxpool parameters, and so much more).