CSC-FPX4030 Introduction to Machine Learning
Learners investigate modern techniques and workflows for training, testing, and applying machine learning models in this introductory course. Learners gain an understanding of industry standard ML frameworks, including TensorFlow, PyTorch, and Keras. Learners explore foundational training methodologies such as supervised, unsupervised, and reinforcement learning; neural and deep-neural networks; and clustering and ensemble methods. Learners utilize open-source image and structured data sets to evaluate the effects of over-fitting and generalization on model performance.