Advanced Machine Learning

This course covers various topics in advanced machine learning. Topics may include optimization algorithms, Python libraries for ML, principles for applied supervised and unsupervised learning, hyperparameter selection, computational trade-offs, modern neural network architectures such as ConvNets, LSTMs, and transformers for computer vision and natural language processing, and deep learning for LLMs.