Machine Learning Classifications and Their Applications(機器學習分類及各自應用)

Supervised & Unsupervised Learning

演算法

開發框架

深度學習

機器學習步驟 ; Feature Engineering ; Cross Validation

模型評估 : Loss function ; Confusion Matrix

模型誤差來源：Bias、Variance、Noise

Underfitting vs Overfitting ; 正規化 ; 降維模型

Activation Function

[平台策略 PaaS ](https://alvislu01.notion.site/PaaS-548bc5b5bdbb4a808ab3bc3786e54969)

[LDA (Latent Dirichlet Allocation)](https://alvislu01.notion.site/LDA-Latent-Dirichlet-Allocation-3235d429d3ef40969ca00d7f76154332)

[神經輻射場 (Neural Radiance Fields；NeRF)](https://alvislu01.notion.site/Neural-Radiance-Fields-NeRF-db54faf0f35b4d67bc53b001fdf81456)

麥當勞

[**模型的可解釋性與公平性(產業）**](https://alvislu01.notion.site/3570b961e6ff44999d7ef84cfbb10403)