alisher-ai / machine-learning-notes

My personal notes on Machine Learning

Personal notes on Machine Learning courses/books/papers with annotations

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Natural Language Processing Specialization notes @ coursera.org taught by deeplearning.ai

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Machine Learning course notes @ coursera.org taught by Andrew Ng

Around 5 years ago, when I started my Machine Learning journey, this course was my first supervisor. Here I wanted to share my lecture notes I have taken at that time: coursera-machine-learning-lecture-notes

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Object detection papers with annotations

I will be sharing the papers I am reading. The shared files would be the original pdf files (paper itself) with annotations: notes, visualizations, brief explanation of various terms and brief summary of related papers.

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AI and cognitive science related papers with annotations

Cognitive science and artificial intelligence (AI) have a long-standing shared history. Early research in AI was inspired by human intelligence and shaped by cognitive scientists. At the same time, efforts in understanding human learning and processing used methods and data borrowed from AI to build cognitive models that mimicked human cognition.

Source: BAICS workshop

machine-learning-notes's Issues

Thanks

I know this is not the perfect place but I am new to Computer Vision and I am loving the style of your notes. I just downloaded and will print this yolov1 paper. Thanks.

RetinaNet TL;DR

In the TL;DR of RetinaNet, you say:

Propose smooth L1 loss to eliminate class imbalance problem in one-stage detectors.

I think you wanted to say focal loss instead of smooth L1.