In this course, "Interpretability in AI", you will learn about various interpretable and explainable machine learning algorithms, a branch of machine learning and AI. This course covers everything you need to know about interpretability, including an overview of basic concepts of interpretability, interpretable models, model-agnostic methods, and example-based explanations. You will also learn how to […]
Parallelism in Deep Learning In this course, “Parallelism in Deep Learning,” you will learn about the need for parallelism in deep learning and how to use different methods of parallelism […]
Self-Supervised Learning Dive into the cutting-edge world of self-supervised learning (SSL) for computer vision in this dynamic and hands-on course. SSL is revolutionizing AI by enabling models to learn from […]
Mastering PyTorch Master PyTorch, an open-source deep learning framework for AI. This course covers everything from the Tensors computations, custom architectures, and advanced functions in PyTorch. It also covers how […]
