Introduction to Data Analysis: Path Classification Experiment. 本资源以选择最优路径为例详细介绍了如何解决一般的分类问题，包括原始数据的探索、模型的构建、模型调优和模型预测分析。包含前馈神经网络（Keras）、机器学习模型（sklearn）和绘制数据图表（matplotlib）的基础使用。
This resource gives an example of how to solve the general classification problem by selecting the optimal path, including the exploration of raw data, model construction, model tuning and model prediction analysis. It includes the basic use of feedforward neural networks (Keras), machine learning models (sklearn), and drawing data charts (matplotlib).