贝叶斯分类器

python的小波变换，多种母波，根据自己的需求进行调用，多加修改成自己的即可。可以作为一维和二维的图像进行去噪处理等，一维信号的去噪也可用。

说明：  深度学习目标检测的yolov3,可以直接拿来作为目标检测的模型(Yolov3 for deep learning target detection)

说明：  Python数据预处理示例，包括数据清洗、数据整合、数据变换等操作。(Python data preprocessing examples, including data cleaning, data integration, data transformation and other operations.)

SVR源码以及详细交通流预测模型，里面有SVM，SVR，LSSVM(SVR source code and detailed traffic flow prediction model, including SVM, SVR, LSSVM)

python读取cloudsat卫星数据并画图(Python reads CloudSat satellite data and draws pictures.)

说明：  对csv文件进行读取并按照一定规则进行数据清洗(Read the CSV file and clean the data according to certain rules)

用python编的爬虫小程序，希望大家喜欢，谢谢大家！(python internet reptile book)

python实现对视屏处理进行欧拉放大，实现颜色和动作放大(Implementation EVM for Python)

说明：  机器学习是人工智能研究领域中的一个极其重要的方向。在现今大数据时代的背景下，捕获数据并从中萃取有价值的信息或模式，使得这一过去为分析师与数学家所专属的研究领域越来越为人们瞩目。本书通过精心编排的实例，切入日常工作任务，摒弃学术化语言，利用高效可复用的Python 代码阐释如何处理统计数据，进行数据分析及可视化。读者可从中学到一些核心的机器学习算法，并将其运用于某些策略性任务中，如分类、预测及推荐等。(Machine learning is an extremely important direction in the field of artificial intelligence research. In the context of the current era of big data, capturing data and extracting valuable information or patterns from it has made this research area that was exclusive to analysts and mathematicians more and more attractive. Through well-organized examples, this book cuts into daily work tasks, abandons academic languages, and uses efficient and reusable Python code to explain how to process statistical data, perform data analysis and visualization. Readers can learn some core machine learning algorithms and apply them to certain strategic tasks, such as classification, prediction, and recommendation.)

说明：  各种聚类方法的python代码，包括k_means聚类以及实现过程(Python code for various clustering methods, including k_means clustering and implementation procedures)