球形CNN的pytorch实现

说明：  深度学习的中文版本，里面详细介绍了深度学习的各种算法，其中还有一些用到的基础内容，例如矩阵和向量的范数(Chinese version of the depth of learning, which detailed the depth of learning algorithms, some of which used the basics, such as vector and matrix norm)

说明：  2010CB945500-组织干细胞识别、谱系重编程和示踪研究——相关学习资料，仅供个人学习参考，禁止用于商业目的(2010 CB945500 - Tissue Stem Cell Recognition, Genealogical Reprogramming and Tracer Research - Relevant Learning Materials for Individual Learning Reference only, Banned for Commercial Purpose)

zhouzhihua machine learning book

说明：  通过python进行编程，运用贝叶斯算法原理，对iris数据集进行分类(Classification of iris data sets by Bayes)

基于深度强化学习的FlappyBird小游戏python实现。

采用Python写的abaqus自动提取应力结果的命令(A command written by Python to automatically extract stress results from ABAQUS)

wxPythonInAction一书及其源代码，内容详尽(The book of wxPythonInAction,with its original codes,being very well detailed)

旨在系统介绍人工智能的基本原理、方法和技术，并反映国内外研究和应用的最新进展(The purpose of this paper is to systematically introduce the basic principles, methods and techniques of AI, and to reflect the latest research and application progress at home and abroad.)

说明：  对无标签的银行数据进行聚类打标，进行数据分析(Cluster and mark the unlabeled bank data and analyze the data)

说明：  分类器的性能比较与调优: 使用scikit-learn 包中的tree，贝叶斯，knn，对数据进行模型训练，尽量了解其原理及运用。 使用不同分析三种分类器在实验中的性能比较，分析它们的特点。 本实验采用的数据集为house与segment。(Performance comparison and optimization of classifiers: We use tree, Bayesian and KNN in scikit-learnpackage to train the data model and try to understand its principle and application. The performances of three classifiers are compared and their characteristics are analyzed. The data set used in this experiment is house and segment.)