python实现PPT自动编号

说明：  隐马尔科夫实现，包含forward-hmm, Viterbi-hmm, Baum-Welch-hmm(Hidden Markov implementation, including forward-hmm, Viterbi-hmm, Baum-Welch-hmm)

Python编程实现股票自动交易，提供一个测试例子以供参考(Python Programming to Realize Stock Automatic Trading)

利用Python实现特征的MinMax标准化和Z-Score标准化两种特征归一化方法。并用原特征、两种归一化特征分别进行朴素贝叶斯模型训练，比较模型性能。(Two normalization methods of MinMax normalization and Z-Score standardization are implemented by Python. The naive Bayes model is trained with the original features and two normalization features respectively to compare the performance of the model.)

该资源是通过给定的维度来生成柯西矩阵的python代码，其中是通过有限域来进行的，因为有限域的运算规则与平常我们所接触到的数学里的运算规则是不一样的，所以我们需要首先将维度转换成有限域里的运算，然后再根据柯西矩阵的规则来生成柯西矩阵。

这是一个基于python 的简单的加密解密软件实例，其中包括一些简单的 tkinter 界面应用。

说明：  sigcomm2019论文合集,供大家参考，还有cvpr合集后续上传，使用模型开发跨平台。网络范围的数据平面编程，SmartNIC上的交互式无服务器计算(sigcomm2019 Paper Collection)

说明：  用Python实现了网页数据的抓取，网页动态图的浮现，字体颜色大小的改变，网页数据爬取，制作相关网页，用表格体现，并改变了表格的风格，(Python is used to capture web page data, the emergence of dynamic graph, the change of font size, the crawl of web page data, the production of relevant web pages, which are represented by tables, and the style of tables is changed.)

说明：  伯克利课程 dqn神经网络 深度学习 吃豆人游戏(Berkeley courses Neural network dqn Deep learning Pac Man Game)

说明：  本书由Keras之父、现任Google A工智能研究员的弗朗索瓦?肖莱（Frangois Chollet）执笔，详尽介 绍了用Python和Keras进行深度学习的探索实践，涉及计算机视觉、自然语言处理、生成式模型等应用。 书中包含30多个代码示例，步骤讲解详细透彻。由于本书立足于人工智能的可达性和大众化，读者无须 具备机器学习相关背景知识即可展开阅读。在学习完本书后，读者将具备搭建自己的深度学习环境、建立 图像识别模型、生成图像和文字等能力(This book is written by Frangois Chollet, the father of keras and the current researcher of Google a intelligence. It introduces in detail the exploration and practice of deep learning with Python and keras, involving computer vision, natural language processing, generative model and other applications. The book contains more than 30 code examples, and the steps are detailed and thorough. Because this book is based on the accessibility and popularization of artificial intelligence, readers can read it without having the background knowledge of machine learning. After learning this book, readers will have the ability to build their own deep learning environment, establish image recognition model, and generate images and characters)

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