ECE 580G Deep Learning for ECE
(Slides and code coming soon)
Lecture 
Slides 
Video 
Code 
Introduction to Object Oriented Programing 



Introduction to learning theory 



Introduction to Numerical Optimization (1) 



Introduction to Numerical Optimization (2) 



Introduction to TensorFLow 2.x (1) 



Introduction to TensorFLow 2.x (2) 



A visual understanding of MLP 



Convolutional Neural Networks 



Convolutions from the brain to the GPU 



Advanced Convolutional Neural Networks 



The inverted residual block  Layers subclassing 



tf.data  Image Augmentations 



Transfer Learning 



A discussion with Eugene Khvedchenya (Albumentations) 



Image Segmentation 



Grad Cam 



Introduction to Generative Adversarial Networks 



ECE 566 Detection Theory
(Spring 2020) I served as coinstructor in Prof. Jessica Fridrichâ€™s ECE 566 Detection Theory. Helped with making slides and/or given a few lectures on the following subjects:
Lecture 
Slides 
Introduction to Mixture Models 

Maximum Likelihood Estimation 

\chi square distribution 

Bayesian Hypothesis Testing (binary) 

Bayesian Hypothesis Testing (multiple hypotheses) 

Bayesian Hypothesis Testing (2 deterministic signals) 

Bayesian Hypothesis Testing (multiple deterministic signals) 

Introduction to Composite Hypothesis Testing 

Introduction to Composite Hypothesis Testing 

Composite Hypothesis Testing (bayesian approach) 

Composite Hypothesis Testing (GLRT) 

Asymptotic distribution of the GLRT 
