关于写作规范及相关资源,见writing
目录。
gantt
dateFormat MM-DD
title 书籍写作时间安排
初稿撰写 : active, des1, 04-26, 05-15
范瑞龙:1-深度学习历史,2-人工神经网络
王纪元:3-卷积神经网络,4-卷积网络的进化
刘源:5-循环神经网络,6-自编码器
苏萌:7-搭建自己的深度学习框架
张志伟:8-深度学习系统,9-如何构建应用
王璇:10-优化算法分析
吴波:11-调参策略
覃一航:12-迁移学习
伊浩源:13-生成对抗网络
张江源:14-深度学习真的是黑盒么
张译:15-图神经网络
王旭:16-从注意力机制到BERT
对于写作规范方面的问题,通过这些渠道反馈:
- 直接私我
- 在仓库里提issue
- CMSC5711 Image Processing and Computer Vision
- CS230 Deep Learning
- CSC 321 Intro to Neural Networks and Machine Learning
- CMU-10707 - Deep Learning
- Blog - Calculus on Computational Graphs: Backpropagation 计算图、反向传播
- YouTube - 李宏毅 Computational Graph & Backpropagation 计算图、反向传播
- (已失效)Machine learning models on a remote Hadoop cluster
- GitHub - HuaizhengZhang/Awesome-System-for-Machine-Learning:一些机器学习系统相关研究的精选,以及论文笔记
- Blog - CSE 599W 课程笔记
- Blog - Deep Learning on Hadoop 2.0
- Blog - 一文读懂Depthwise卷积
- Blog - Evolution of Graph Computation and Machine Learning
- Deep Learning From Scratch: Theory and Implementation
- Deep Learning From Scratch I: Computational Graphs 计算图
- Computational Graphs 计算图
- Dynamic vs Static Computational Graphs – PyTorch and TensorFlow 动态、静态计算图
- Blog - On chain rule, computational graphs, and backpropagation 链式法则、计算图、反向传播
- Computational Graphs in Deep Learning 计算图
- StackExchange - What is a Dynamic Computational Graph? 动态计算图
- GitHub - v-iashin/CS231n PyTorch/Tensorflow solutions for Stanford's CS231n: "CNNs for Visual Recognition"
- Blog - Hyperparameter Tuning in Python: a Complete Guide 调参指南
- Blog - Understanding Graph Convolutional Networks for Node Classification 图卷积网络
- Blog - Graph Convolutional Networks 图卷积网络
- Blog - 深度学习发展史
- OPEN MLSYS 机器学习系统:设计和实现 开源书籍