readlist

 

Why ML interfaces will be more like pets than machines	https://petewarden.com/2018/05/07/why-ml-interfaces-will-be-more-like-pets-than-machines/
Deep Learning is Eating Software	https://petewarden.com/2017/11/13/deep-learning-is-eating-software/
What are GPUs, anyway?	https://petewarden.com/2016/05/17/what-are-gpus-anyway/
Why Low-Power NN Accelerators Matter	https://petewarden.com/2018/02/26/why-low-power-nn-accelerators-matter/
How many images do you need to train a neural network?	https://petewarden.com/2017/12/14/how-many-images-do-you-need-to-train-a-neural-network/
How do CNNs Deal with Position Differences?	https://petewarden.com/2017/10/29/how-do-cnns-deal-with-position-differences/
What I’ve learned about neural network quantization	https://petewarden.com/2017/06/22/what-ive-learned-about-neural-network-quantization/
How to Quantize Neural Networks with TensorFlow	https://petewarden.com/2016/05/03/how-to-quantize-neural-networks-with-tensorflow/
Why GEMM is at the heart of deep learning	https://petewarden.com/2015/04/20/why-gemm-is-at-the-heart-of-deep-learning/
An Engineer’s Guide to GEMM	https://petewarden.com/2015/10/25/an-engineers-guide-to-gemm/

 

Deep Learning for Computer Vision with Caffe and cuDNN	https://devblogs.nvidia.com/deep-learning-computer-vision-caffe-cudnn/

 

DeepFace closing the gap to human level performance

CS231n Convolutional Neural Networks for Visual Recognition	http://cs231n.github.io/

基于深度学习的目标检测技术演进：R-CNN、Fast R-CNN、Faster R-CNN	https://www.cnblogs.com/skyfsm/p/6806246.html