CityEngine-Philadelphia_example案例操作详解

FullCalendar示例项目 一组简单的示例项目，展示了如何在各种构建设置中使用FullCalendar。 请阅读每个项目子目录中的自述文件。

从swfupload官网下载 MIT协议 支持 flashplayer8 到 10

Python Machine Learning By Example by Yuxi (Hayden) Liu English | 31 May 2017 | ASIN: B01MT7ATL5 | 254 Pages | AZW3 | 3.86 MB Key Features Learn the fundamentals of machine learning and build your own intelligent applications Master the art of building your own machine learning systems with this example-based practical guide Work with important classification and regression algorithms and other machine learning techniques Book Description Data science and machine learning are some of the top buzzwords in the technical world today. A resurging interest in machine learning is due to the same factors that have made data mining and Bayesian analysis more popular than ever. This book is your entry point to machine learning. This book starts with an introduction to machine learning and the Python language and shows you how to complete the setup. Moving ahead, you will learn all the important concepts such as, exploratory data analysis, data preprocessing, feature extraction, data visualization and clustering, classification, regression and model performance evaluation. With the help of various projects included, you will find it intriguing to acquire the mechanics of several important machine learning algorithms – they are no more obscure as they thought. Also, you will be guided step by step to build your own models from scratch. Toward the end, you will gather a broad picture of the machine learning ecosystem and best practices of applying machine learning techniques. Through this book, you will learn to tackle data-driven problems and implement your solutions with the powerful yet simple language, Python. Interesting and easy-to-follow examples, to name some, news topic classification, spam email detection, online ad click-through prediction, stock prices forecast, will keep you glued till you reach your goal. What you will learn Exploit the power of Python to handle data extraction, manipulation, and exploration techniques Use Python to visualize data spread across multiple dimensions and extract useful features Dive deep into the world of analytics to predict situations correctly Implement machine learning classification and regression algorithms from scratch in Python Be amazed to see the algorithms in action Evaluate the performance of a machine learning model and optimize it Solve interesting real-world problems using machine learning and Python as the journey unfolds About the Author Yuxi (Hayden) Liu is currently a data scientist working on messaging app optimization at a multinational online media corporation in Toronto, Canada. He is focusing on social graph mining, social personalization, user demographics and interests prediction, spam detection, and recommendation systems. He has worked for a few years as a data scientist at several programmatic advertising companies, where he applied his machine learning expertise in ad optimization, click-through rate and conversion rate prediction, and click fraud detection. Yuxi earned his degree from the University of Toronto, and published five IEEE transactions and conference papers during his master's research. He finds it enjoyable to crawl data from websites and derive valuable insights. He is also an investment enthusiast. Table of Contents Getting Started with Python and Machine Learning Exploring the 20 newsgroups data set Spam email detection with Naive Bayes News topic classification with Support Vector Machine Click-through prediction with tree-based algorithms Click-through rate prediction with logistic regression Stock prices prediction with regression algorithms Best practices

感觉比rust编程指南之类循规蹈矩的书籍更容易上手。 毕竟呆头呆脑地学几天语法的成本太高了。 建议直接读所需要的项目的代码，不懂的语法直接查这本书。

几个用java写的小程序，实现了bio和nio

The Python Standard Library by Example --Doug Hellmann 那本的源代码哟，欢迎下载！

Matlab读取BMP文件代码示例CUDA物理项目141/241 大卫·摩尔（David Moore）更新于2019年2月4日。 此代码按原样对10,000个粒子运行O（n ^ 2）CUDA模拟。 Galaxy1.txt是一个包含100,000个粒子的星系，并且在kernel.cu中将“ nSkip”设置为10，这意味着每获取十分之一粒子，其质量便乘以10。 编译说明 要运行，请将所有文件解压缩到目录中。 打开终端并cd进入目录。 然后输入“ make run”。 这会： 创建“ out”目录。 将kernel.cu编译为nbody可执行文件 运行./nbody，它输出30个.bmp文件 使用convert将位图放入.gif中 源代码如何工作： 大约50行kernel.cu是CUDA代码，其余是C ++。 ImageUtil.cpp和ImageUtil.h是我为输出图像编写的一些低质量实用程序。 我不建议您在项目中使用它们，但是它们对于调试很有用。 最好像往常一样在matlab或python中进行绘图。 在尝试简化三个单独的资源时编写了源代码文件kernel.cu . GPU Gems

Netty是业界最流行的nio框架之一，结合springboot可以满足快速开发，MQTT（Message Queuing Telemetry Transport，消息队列遥测传输协议），是一种基于发布/订阅（publish/subscribe）模式的"轻量级"通讯协议，该协议构建于TCP/IP协议上的。MQTT协议的可以用在物联网、小型设备、还有移动应用上，Netty也可以实现MQTT协议，他的内部封装了MQTT协议的相关对象，使用Netty+SpringBoot方式可以快速地开发一套基于MQTT协议(主要是MQTT3.1和MQTT3.1.1)的服务端程序。 https://blog.csdn.net/myyhtw/article/details/114041042

目录 一、mapper接口中的方法解析 二、example实例解析 三、应用举例 1.查询 2.插入数据 3.更新数据 4.删除数据 5.查询数据数量 一、mapper接口中的方法解析 mapper接口中的函数及方法 方法 说明 int countByExample(UserExample example) thorws SQLException 按条件计数 int deleteByPrimaryKey(Integer id) thorws SQLException 按主键删除 int deleteByExample(UserExample example) thorws