Neural Structured Learning in TensorFlow

This course aims to teach learners how to utilize the Neural Structured Learning (NSL) framework in TensorFlow for training neural networks with structured signals. By the end of the course, students will be able to construct accurate and robust models for tasks such as vision, language understanding, and prediction. The course covers topics such as the advantages of learning with structure, neural graph learning, model robustness, adversarial learning, and hands-on tutorials. The intended audience for this course includes both novice and advanced developers interested in enhancing their skills in training neural networks using structured signals in TensorFlow.