LIST OF EXERCISES
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1. Train a deep neural network for an Image classification task.
2. Apply convolutional neural network for the same image classification dataset and compare
DNN and CNN in terms of parameters and performance.
3. Construct an object detector using convolutional neural network.
4. Develop an image segmentation model using a fully convolutional network.
5. Demonstrate the use of Autoencoder for dimensionality reduction
6. Train a convolutional autoencoder for image reconstruction.
7. Apply denoising Autoencoder for noise removal and obtain clean images.
8. Implement image captioning using recurrent neural network.
9. Design an LSTM based handwriting recognition model.
10. Compare the performance of RNN, LSTM and GRU in prediction of time series data.
11. Train a generative adversarial network with a sample image dataset and analyse the
generated images.
12. Implement deep reinforcement learning algorithm for dynamic prediction.