Deep Learning Course Assignments

Description

A1.

• Implementing a neural network from scratch using Numpy toolbox.

A2.

• Saliency map prediction of images by Deep Convnet model.
• Reconstraction of images by thier feature maps from different layers of AlexNet.

A3.

• Brain tumor tissue seperation in MRI pictures by image segmentation with U-Net model.
• Part-Of-Speech (POS) tagging with RNNs.

A4.

• Using DistilHuBert transformer model for speech-to-text and keyword spotting tasks
• Using DistilBert and XLM transformer models for question-answering task

Technologies Used

The main framework used for almost every assignment is Pytorch.