Understanding Deep Learning Research Tutorial - Theory, Code and Math
Taha GÖÇER
About this course
This comprehensive tutorial demystifies deep learning research by guiding learners through the critical skills of reading technical papers, understanding mathematical notation, and navigating research code bases. By leveraging recent research papers, including the QH Adam optimizer and segmentation models, the course provides practical examples and a structured approach to comprehend dense mathematical content effectively.
What you should already know
A basic understanding of machine learning concepts is required before taking this course.
What you will learn
By the end of this tutorial, learners will be equipped with the skills to effectively read and understand deep learning research papers and their corresponding code, enabling them to reproduce and apply cutting-edge AI techniques.