Deep Learning

These are my notes on refreshing my object detection knowledge. We will start with bounding boxes for localization and cover everything we need before jumping in to implement YOLO algorithms. This tutorial includes answers to the following questions: What is localization? What are a bounding box and sliding window? How to measure the success of a predicted bounding box: Intersection over the union. How to get rid of extra bounding boxes: Non-max suppression....

This post includes my notes from the lecture “Makemore Part 3: Activations & Gradients, BatchNorm” by Andrej Karpathy. Link of the video: https://www.youtube.com/watch?v=P6sfmUTpUmc Initialization Fixing the initial Loss: Initial loss must be arranged (the value depends on the question), in our case its a uniform probability. When initializing make sure the numbers do not take extreme values (* .01) Do not initialize to 0 Having 0 and 1 in softmax (a lot of them) is really bad, since the gradient will be 0 (vanishing gradient)....