Hello there 👋 I hear that you are learning Deep Learning! That's amazing!
This is a selection of resources from Binghamton University's EECE580G - Deep Learning for ECE course.
Resources and teaching by Yassine Yousfi (me) Jan Butora and Prof. Jessica Fridrich.
[Contributing] Many notebooks are mostly code cells, those were presented and commented on during class. If you're watching the videos and taking note, please do not hesitate to do so in the notebooks and open a PR. I will be happy to review it.
This is far from being a complete guide to Deep Learning. Covering all aspects of Deep Learning, while also working on practical examples is challenging.
For a more complete course, I encourage you to check:
| 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 | 📕 | 📹 | 📘 |