Learning Materials

1. Why Momentum Really Works: distill.pub/2017/moment…

2. A Visual Proof that Neural Nets Can Compute any Function: neuralnetworksanddeeplearning.com/chap4.html

Deep Learning

1. Deep Learning using Linear Support Vector Machines: arxiv.org/abs/1306.02…

CNN

1. AlexNet: www.cs.toronto.edu/~fritz/absp…
2. ZFNET: arxiv.org/abs/1311.29…
3. VGG: arxiv.org/abs/1409.15… and 最详细的VGG模型理解-CSDN and 【精读AI论文】VGG深度学习图像分类算法】
4. Network in Network: arxiv.org/abs/1312.44… and 深度学习（二十六）Network In Network学习笔记 and【机器学习】关于CNN中1×1卷积核和Network in Network的理解
5. GooLeNet: arxiv.org/abs/1409.48… and 【论文研读】GoogLeNet-Going deeper with convolutions
6. MobileNet: arxiv.org/abs/1704.04… and
7. SqueezeNet: arxiv.org/abs/1602.07… and 公开代码 and 四大经典轻量级网络之二：SqueezeNet

Model Compression

1. Learning both Weights and Connections for Efficient Neural Networks: arxiv.org/abs/1506.02…

Acceleration

1. cuDNN: Efficient Primitives for Deep Learning: arxiv.org/abs/1410.07… and cuDNN: Efficient Primitives for Deep Learning 论文阅读

FPGA

1. Going Deeper with Embedded FPGA Platform for Convolutional Neural Network: dl.acm.org/doi/10.1145…

TinyML

Dataset

1. Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition: Note

2. MIMII Dataset: Sound Dataset for Malfunctioning Industrial Machine Investigation and Inspection: arxiv.org/abs/1909.09… and Note

3. Visual Wake Words Dataset: arxiv.org/abs/1906.05… and Paper with Code and Note

System and Framework

1. CMSIS-NN: Efficient Neural Network Kernels for Arm Cortex-M CPUs: Note

2. Machine Learning on Arm Cortex-M Microcontrollers: Note

3. TensorFlow Lite Micro: Embedded Machine Learning for TinyML Systems: proceedings.mlsys.org/paper_files…

Keyword Spotting

Project

1. CS231n: cs231n.stanford.edu/index.html and Assignment Github