电力系统分析之短路电流计算

java虚拟机规范(java hypothesized machine standard )

Matlab基础及其应用教程,入门级教程，包括平台简介以及基础的语法(Matlab foundation and its application tutorial, introductory tutorial, including platform introduction and basic grammar)

《通信原理》习题参考答案 樊昌信编的第5版的1-5章习题解答("Communication Theory" Fan answer the questions reference letter series version 5 1-5 Chapter answer Exercises)

电子工程师应掌握的二十种基本模拟电路，基本电路(Twenty basic analog circuits that electronic engineers should master, Twenty basic analog circuits that electronic engineers should master)

nRF24E1通信相关的源程序！很有帮助！(nRF24E1 communication-related source code! Very helpful!)

说明：  一款C语言代码方法搜索手册，方便写代码的字典(A C language code method search manual, easy to write code dictionary)

python算法资料，提供了不少关于python的算法，值得一看。(Python algorithm data, provide a lot of Python algorithm, it is worth seeing.)

C# programmers: no more translating data structures from C++ or Java to use in your programs! Mike McMillan provides a tutorial on how to use data structures and algorithms plus the first comprehensive reference for C# implementation of data structures and algorithms found in the .NET Framework library, as well as those developed by the programmer. The approach is very practical, using timing tests rather than Big O notation to analyze the efficiency of an approach. Coverage includes arrays and array lists, linked lists, hash tables, dictionaries, trees, graphs, and sorting and searching algorithms, as well as more advanced algorithms such as probabilistic algorithms and dynamic programming. This is the perfect resource for C# professionals and students alike.

java五子棋程序源代码,java五子棋程序源代码

机器学习实战（高清 中文版） 作者： Peter 本书通过精心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。本书适合机器学习相关研究人员及互联网从业人员学习参考。(Machine learning combat (HD Chinese version) Author: Peter This book cuts into everyday tasks through elaborate examples. Abandoning academic language uses efficient and reusable Python code to illustrate how to process statistics for 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. This book is suitable for machine learning related researchers and Internet practitioners to learn reference.)