Deep Learning Projects

This repository contains a collection of my deep learning projects, assignments, and experiments.

Projects

• Audio Separation (audio sep/): A project focused on separating audio sources from a mixed signal.
• Encoder-Decoder Models (Encoder_decoder/, Encoder_decoder_Bidirectional_lstm/): Implementations of encoder-decoder architectures, including bidirectional LSTMs, for tasks like machine translation.
• LSTM Name Classification (LSTM/): A Long Short-Term Memory (LSTM) network to classify names into their language of origin.
• RNN Models (RNN/, RNN-recursive/): Projects exploring Recurrent Neural Networks for sequence-based tasks.
• Transformer Models (transformer/): Implementations of the Transformer architecture, likely for translation or other sequence-to-sequence tasks.

Assignments

A series of Jupyter notebooks covering various deep learning topics:

• Assignment02.ipynb
• Assignment03.ipynb
• Assignment04.ipynb
• Assignment05.ipynb
• Assignment06.ipynb
• Assignment07.ipynb
• Assignment08.ipynb

Saved Models

The repository also contains several saved model weights (.pth files) from different optimizers and training runs, such as:

• Adagrad_model.pth
• Adam_model.pth
• RMSprob_model.pth
• SGD_model.pth
• and others.

Datasets

The data/ directory contains datasets used in the projects, including:

• FashionMNIST
• MNIST