This repository contains the programming assignments and projects from the course EEL 6814 at the University of Florida.
Nonlinear modeling using neural networks. Gradient descent learning in the additive neural model. Statistical Learning Concepts. Information theoretic cost functions. Convolution neural networks. Recurrent neural networks. Foundations of Deep Learning. Importance of Deep learning for representation. Current models for image and speech recognition. Adversarial Networks. Transformers. Challenges of Deep Learning.
Understand and utilize the concepts of machine learning for data science and electrical engineering. Focus on tools for multivariate data analysis and how to handle uncertain data with probability models. Both static and time varying data fitting and classification problems will be covered. Neural network implementations will also be used in the course.
Please note that encodings.py file in Project 2 is too large to upload. Therefore, it is only available upon request.