stm32单片机使用can通信控制Maxon电机的相关代码及Maxon相关手册

获取wifi连接信息，IP，MAC地址，设置wifi 为静态IP，子网掩码，mac地址等设置，https://blog.csdn.net/qq_35345103/article/details/84449897

相机标定相关代码，注释掉的是其他功能

以jupyter为平台，利用python实现对墨尔本10年气候变化数据集的特征处理，然后并利用机器学习模型进行训练以及对原始数据集的拟合，最后来评价那种模型的拟合效果最佳。（提供了相关数据集）

The Python code and supporting material, including example data files, are available as a single ZIP compressed archive. This must be uncompressed before use and will extract into a folder (directory) called "PythonForBiology", inside which the Python files, ending in ".py", and various sub-folders can be found. This arrangement of files and folders will allow the Python code to run directly from inside the uncompressed "PythonForBiology", i.e. the locations of any modules or data files mentioned in the code (and book) are specified relative to this location. The "examples" sub-folder contains all of the data files that are used as examples to support the Python code described in the book. The "databases" sub-folder relates to Chapter 20 and contains SQL and Python files sub-divided into sections to support both SQLite and MySQL database implementations. The "speedy" folder relates to Chapter 27 and contains code relevant to the binding of fast functions written in the C or Cython languages, including any files required for compilation. Many of the book chapters have a corresponding Python file containing the completed scripts and programs for that chapter. These files may be run directly as Python to test the code they contain. Note that several of these files will not work isolation, given that they import functionality from the others, which are assumed to be in the same folder. Chapters 1-4 and 10 do not have a corresponding Python file given that they only discuss the code in terms of short or incomplete fragments.

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来源于GitHub，代码中的bug修复过了，代码是比较实用的，收费是因为修复了bug，添加了需要用到的dll