Deep Learning: Model Optimization and Tuning
Deep Learning: Model Optimization and Tuning
.MP4, AVC, 1280x720, 30 fps | English, AAC, 2 Ch | 54m | 149 MB
Instructor: Kumaran Ponnambalam
.MP4, AVC, 1280x720, 30 fps | English, AAC, 2 Ch | 54m | 149 MB
Instructor: Kumaran Ponnambalam
Deep Learning as a technology has grown leaps and bounds in the last few years. More and more AI solutions use Deep Learning as their foundational technology. Studying this technology, however, presents several challenges. IT professionals from varying backgrounds need a simplified resource to learn the concepts and build models quickly.
In this course, instructor Kumaran Ponnambalam provides a simplified path to understand various optimization and tuning options available for deep learning models and shows you how to use these options to improve models. He begins by reviewing Deep Learning, including artificial neural networks and architectures. Next, Kumaran discusses the process of hyper parameter tuning. He examines the building blocks of neural networks and the levers available to tune them. Kumaran offers recommendations and best practices. Then he concludes with an end-to-end tuning example.
Deep Learning: Model Optimization and Tuning
