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# System prepended metadata

title: 捌、參考文獻

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# 捌、參考文獻
- 高中生也看得懂 機器學習的數學基礎
- 學AI真簡單(I)：初探機器學習-從認識AI到Kaggle競賽
- 學AI真簡單(II)：動手做深度學習-揭開神經網路的面紗
- 再強一點：用Go語言完成六個大型專案
- C++程式設計第三版
- [build artificial neural network scratch part 1](https://www.kdnuggets.com/2019/11/build-artificial-neural-network-scratch-part-1.html)
- [機器/深度學習-基礎數學(二):梯度下降法(gradient descent) | by Tommy Huang | Medium](https://chih-sheng-huang821.medium.com/%E6%A9%9F%E5%99%A8%E5%AD%B8%E7%BF%92-%E5%9F%BA%E7%A4%8E%E6%95%B8%E5%AD%B8-%E4%BA%8C-%E6%A2%AF%E5%BA%A6%E4%B8%8B%E9%99%8D%E6%B3%95-gradient-descent-406e1fd001f)
- [機器/深度學習-基礎數學(三):梯度最佳解相關算法(gradient descent optimization algorithms) | by Tommy Huang | Medium](https://chih-sheng-huang821.medium.com/%E6%A9%9F%E5%99%A8%E5%AD%B8%E7%BF%92-%E5%9F%BA%E7%A4%8E%E6%95%B8%E5%AD%B8-%E4%B8%89-%E6%A2%AF%E5%BA%A6%E6%9C%80%E4%BD%B3%E8%A7%A3%E7%9B%B8%E9%97%9C%E7%AE%97%E6%B3%95-gradient-descent-optimization-algorithms-b61ed1478bd7)
- [自动微分(Automatic Differentiation)简介_CarlXie-CSDN博客_自动微分](https://blog.csdn.net/aws3217150/article/details/70214422)
- [Backpropagation | Brilliant Math & Science Wiki](https://brilliant.org/wiki/backpropagation/)
- [Backpropagation](http://galaxy.agh.edu.pl/~vlsi/AI/backp_t_en/backprop.html)
- [[機器學習ML NOTE]SGD, Momentum, AdaGrad, Adam Optimizer | by GGWithRabitLIFE | 雞雞與兔兔的工程世界 | Medium](https://medium.com/%E9%9B%9E%E9%9B%9E%E8%88%87%E5%85%94%E5%85%94%E7%9A%84%E5%B7%A5%E7%A8%8B%E4%B8%96%E7%95%8C/%E6%A9%9F%E5%99%A8%E5%AD%B8%E7%BF%92ml-note-sgd-momentum-adagrad-adam-optimizer-f20568c968db)
- [backpropagation - Error function in Artificial Neural Network trained using backpropogation - Stack Overflow](https://stackoverflow.com/questions/22601258/error-function-in-artificial-neural-network-trained-using-backpropogation)
- [自動微分](http://fancyerii.github.io/books/autodiff/)
- [梯度](https://www.youtube.com/watch?v=npkl19rcpdY)
- [方向導數](https://www.youtube.com/watch?v=-DumtBiW4HE)
- [Machine Learning Foundations (機器學習基石) - YouTube](https://www.youtube.com/playlist?list=PLXVfgk9fNX2I7tB6oIINGBmW50rrmFTqf)
- [Backpropagation calculus | Chapter 4, Deep learning](https://www.youtube.com/watch?v=tIeHLnjs5U8)
- [為什麼需要反向傳播(裡面有圖解)](https://allen108108.github.io/blog/2020/06/01/%E7%82%BA%E4%BB%80%E9%BA%BC%E9%9C%80%E8%A6%81%E5%8F%8D%E5%90%91%E5%82%B3%E6%92%AD%20_%20Why%20Backpropagation%20_/)
- [Kohonen Networks]()
- [NVIDIA DOCUMENTATION CENTER](https://docs.nvidia.com/)
- [Rust 程式設計語言](https://rust-lang.tw/book-tw/)
- [syn example](https://github.com/dtolnay/syn/tree/3418c8434539542b1325ebc375cb2cd7560f5277/examples/trace-var)
- [python實作微分樹(建樹) ](https://towardsdatascience.com/build-your-own-automatic-differentiation-program-6ecd585eec2a)