『机器学习』核心概念的可视化解释

👍 『机器学习』核心概念的可视化解释

MLU（ Machine Learning University，机器学习大学）是亚马逊的一项教育计划，旨在教授机器学习理论和实际应用。MLU-Explain 作为计划的一部分，通过可视化这种信息丰富且有趣的方式，讲解了机器学习的重要概念。交互页面的设计非常酷！

https://mlu-explain.github.io/

不过现在涉及的模型不太多，主要有机器学习基本概念（ROC AUC 交叉验证 测试/验证/测试集 准确率 召回率等等），还有简单线性回归、逻辑回归、决策树、随机森林等

Linear Regression Article Image (A Scatterplot showing orange points and a black line on the right. On the left math equations for The Normal Equation).

Logistic Regression Article Image (A Scatterplot showing points for Sunny and Rainy days plotted by Temperature in degrees Fahrenheit and the predicted probability as a sigmoid curve).

ROC & AUC Article Image (A Scatterplot showing three ROC curves: one labeled Perfect Classifier (line hugging left and top of plot), one labeled Our Classifier (bumpy line), and one labeled Random Classifier (diagonal line)).

Cross-Validation Article Image.

Train, Test, Validation Article Image (Groups of cats/dogs in circles).

Precision Recall Article Image (Beeswarm Plot).

Decision Tree Title Image

Decision Tree Title Image

Double Descent Title Image

image-20230113094005562

posted @ 2023-03-06 14:04  机器学习算法与Python  阅读(27)  评论(0)  编辑  收藏  举报