A collection of resources such as lecture slides, blog posts, YT videos., etc, that I found useful for understanding a concept. Does not include research papers.

Pytorch Internals, Tips and Tricks

Neural Networks

1. What is bias in a NN?- https://www.turing.com/kb/necessity-of-bias-in-neural-networks

Object Detection

1. Lil'Log blog posts- https://lilianweng.github.io/posts/2017-10-29-object-recognition-part-1/
2. CV3DST, TUM lecture slides- https://dvl.in.tum.de/slides/cv3dst-ss20/
3. EfficientDet Blog- https://medium.com/@nainaakash012/efficientdet-scalable-and-efficient-object-detection-ea05ccd28427

Metric Learning

1. The Why and the How of Deep Metric Learning.- https://towardsdatascience.com/the-why-and-the-how-of-deep-metric-learning-e70e16e199c0