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[Akankhya-Mohapatra]

• Perform Tensor operations using PyTorch (Tensor squeezing, unsqueezing, viewing, Tensor concatenation and stack, expansion and reduction using torch.squeeze, torch.unsqueeze, torch.Tensor.view, torch.cat, torch.stack, torch.Tensor.expand, torch.Tensor.expand_as, torch.mean, torch.sum, torch.max, torch.min, torch.topk)
• Implement a convolutional neural network for image classification on CIFAR-10 dataset (implemented initialization and forward function using ReLU activation function, tuned hyperparameters and evaluated validation accuracy; added max pooling layer and compared validation accuracies and test accuracy with the best hyperparameter combination)
• implement a recurrent neural network for sentiment analysis, i.e., classifying sentences into given sentiment labels, including positive, negative and neutral using a benchmark dataset SST, train and test the accuracy.