Welcome to CSCI 4701!

This is the website of the CSCI 4701: Deep Learning course taught at ADA University.

Deep Learning focuses on artificial neural networks and how they are trained and optimized. This course covers core concepts starting with backpropagation, including regularization and optimization techniques. Students will gain practical skills using the PyTorch framework and learn neural architectures used in both Computer Vision (CV) and Natural Language Processing (NLP), including Convolutional Neural Networks (CNNs) and Transformer-based models. The course introduces generative modeling with Variational Autoencoders (VAEs) and briefly covers current developments in deep learning, such as Latent Diffusion Models (LDMs) and Large Language Models (LLMs).

You can navigate through the course starting from the introductory overview or directly check the practical notebooks via the navigation bar.