The Nuts and Bolts of Deep Learning Algorithms for Object Detection
For any fans of Deep Learning check out this recent post from Data From The Trenches about the nuts and bolts of deep learning algorithms for object detection. Agustin provides a non-technical overview of the core concepts and methods of deep learning algorithms for object detection.
Please feel free to read and share. I'm curious, what your takeaways are from this piece? Is it helpful for your practice?