MACHINE LEARNING INNOVATIONS

Catalog description

Advanced study of machine learning and deep learning with emphasis on mathematical foundations, optimization, model design, and real-world applications. Topics include supervised, unsupervised, and reinforcement learning; linear algebra and calculus; model training and evaluation; deep neural networks, convolutional networks, recurrent models, transformers, and predictive analysis.