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RSS订阅原创 Python 数据分析 - NumPy
numpynumpy.linspace(start, stop, num=50, endpoint=True)：在[start, stop](endpoint=True)或者[start, stop)(endpoint=False)之间取num个等差的数。import numpy as nparr = np.linspace(0, 10, num=10)print(arr...
2020-02-26 00:40:47
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原创 Statistics 01
data types:1. Quantitative data: numeric values that allow mathematical operations1.1 Continuous data: Quantitative values that can be split into smaller values1.2 Discrete data: Quantitative value...
2020-02-18 18:29:59
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原创 Python 基础
<添加目录>Python语言的特点1. 面向对象语言2. 解释型语言 -- 执行效率低3. 代码简洁，开发效率高4. 丰富的函数库Python语言的使用场景1. web开发2. 网络爬虫3. 网络安全4. 自动化运维5. 数据分析6. 人工智能sublime texthttp://www.sublim...
2020-01-17 01:40:54
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原创 SQL 应用实例
查询总分第六到十名的学生姓名以及总分stud_crs:select sno, sum(grade) as 总分from stud_crsgroup by sno;select top 3 sno, sum(grade) as 总分from stud_crsgroup by snoorder by sum(grade) desc;select top 2 ...
2019-12-19 19:01:25
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原创 SQL JOIN
stud:Course:stud_crs:select stud_crs.scno, stud.sno as 学号, stud.sname as 姓名, stud_crs.cno as 课程号, stud_crs.grade as 分数 from stud inner join stud_crs on stud.sno = stud_crs.sno;...
2019-12-19 14:02:35
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原创 Review 16 [coursera] Machine learning - Stanford University - Andrew Ng
Large Scale Machine LearningAssuming that you have a very large training set, which of thefollowing algorithms do you think can be parallelized usingmap-reduce and splitting the training s...
2019-07-18 15:21:36
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原创 Ex08 [coursera] Machine learning - Stanford University - Andrew Ng
Anomaly Detection and Recommender Systems目录Anomaly Detection and Recommender SystemsAnomaly detectionex8.mestimateGaussian.mmultivariateGaussian.mselectThreshold.mprompt outputfigure...
2019-07-17 12:36:13
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原创 Review 15 [coursera] Machine learning - Stanford University - Andrew Ng
Recommender SystemsIn which of the following situations will a collaborative filtering system be the most appropriate learning algorithm (compared to linear or logistic regression)?You manage an o...
2019-07-16 13:35:17
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原创 Ex07 [coursera] Machine learning - Stanford University - Andrew Ng
K-means Clustering and Principal Component Analysis目录K-means Clustering and Principal Component AnalysisK-means Clusteringex7.mfindClosestCentroids.mcomputeCentroids.mrunkMeans.mkMeans...
2019-05-17 20:26:46
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原创 Review12 [coursera] Machine learning - Stanford University - Andrew Ng
Unsupervised LearningFor which of the following tasks might K-means clustering be a suitable algorithm? Select all that apply.A. From the user usage patterns on a website, figure out what diffe...
2019-05-15 19:14:59
206
原创 Ex06 [coursera] Machine learning - Stanford University - Andrew Ng
Support Vector Machines目录Support Vector MachinesSupport Vector Machinesex6.msvmTrain.mvisualizeBoundaryLinear.mgaussianKernel.mvisualizeBoundary.msvmPredict.mdataset3Params.mProm...
2019-05-14 18:01:05
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原创 Ex05 [coursera] Machine learning - Stanford University - Andrew Ng
Regularized Linear Regression and Bias v.s. Variance目录Regularized Linear Regression and Bias v.s. Varianceex5.mlinearRegCostFunction.mtrainLinearReg.mlearningCurve.mpolyFeatures.mfeatu...
2019-05-05 14:03:20
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原创 Ex04 [coursera] Machine learning - Stanford University - Andrew Ng
Neural Networks Learning目录Neural Networks Learningex4.mdisplayData.mnnCostFunction.msigmoidGradient.msigmoid.mrandInitializeWeights.mcheckNNGradients.mdebugInitializeWeights.mcom...
2019-05-02 17:16:45
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原创 Review08 [coursera] Machine learning - Stanford University - Andrew Ng
Neural Networks: LearningFor computational efficiency, after we have performed gradient checking to verify that our backpropagation code is correct, we usually disable gradient checking before us...
2019-04-27 11:47:10
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原创 Ex03 [coursera] Machine learning - Stanford University - Andrew Ng
Multi-class Classification and Neural Networks目录Multi-class Classification and Neural NetworksExamples from the datasetPart1ex3.mdisplayData.mlrCostFunction.mpredictOneVsAll.mprompt ou...
2019-04-25 13:38:16
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原创 Review07 [coursera] Machine learning - Stanford University - Andrew Ng
Neural Networks: RepresentationAny logical function over binary-valued (0 or 1) inputs x1 and x2 can be (approximately) represented using some neural network. TThe activation values of the hidd...
2019-04-24 19:13:04
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原创 Ex02 [coursera] Machine learning - Stanford University - Andrew Ng
Logistic Regression目录Part1ex2.mplotData.msigmoid.mcostFunction.mplotDecisionBoundary.mpredict.mprompt outputfigure outputPart2ex2_reg.mmapFeature.mcostFunctionReg.mpro...
2019-04-21 15:04:14
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原创 Review05 [coursera] Machine learning - Stanford University - Andrew Ng
Logistic RegressionSuppose you have the following training set, and fit a logistic regression classifier hθ(x)=g(θ0+θ1x1+θ2x2). Which of the following are true? Check all that appl...
2019-04-21 14:10:52
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原创 fminunc() [coursera] Machine learning - Stanford University - Andrew Ng
Advanced Optimizationfminunc() in OctavecostFunction.mfunction [jVal, gradient] = costFunction(theta) jVal = (theta(1)-5)^2 + (theta(2)-5)^2; gradient = zeros(2,1); gradient(1) = 2*(theta...
2019-04-20 15:50:07
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原创 Ex01 [coursera] Machine learning - Stanford University - Andrew Ng
Linear Regression目录Part1ex1.mplotData.mcomputeCost.mgradientDescent.mprompt outputfigure outputPart2ex1_multi.mfeatureNormalize.mcomputeCostMultigradientDescentMulti.mno...
2019-04-20 00:19:48
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原创 Review04 [coursera] Machine learning - Stanford University - Andrew Ng
Octave/Matlab TutorialSay you have two column vectors vvv and www, each with 7 elements (i.e., they have dimensions 7x1). Consider the following code:z = 0;for i = 1:7 z = z + v(i) * w(i)end...
2019-04-18 16:08:44
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原创 Octave/Matlab Tutorial [coursera] Machine learning - Stanford University - Andrew Ng
目录Octave/Matlab TutorialBasic OperationsMoving Data AroundComputing On DataPlotting DataControl Statements: for, while, if StatementsOctave/Matlab TutorialBasic Operationsoctave:1&g...
2019-04-18 15:14:41
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原创 Review03 [coursera] Machine learning - Stanford University - Andrew Ng
Linear Regression with Multiple VariablesSuppose m=4 students have taken some class, and the class had a midterm exam and a final exam. You have collected a dataset of their scores on the two exams,...
2019-04-18 09:52:45
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原创 Review02 [coursera] Machine learning - Stanford University - Andrew Ng
Linear Regression with One VariableIf θ0 and θ1 are initialized at the global minimum, then one iteration will not change their values. T Setting the learning rate α to be very small is not ...
2019-04-12 21:03:33
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原创 OS note04 -- process, thread
#include <stdio.h>#include <unistd.h>int main(){ printf("start from main (pid:%d)\n", (int)getpid()); int rc; rc = fork(); if( rc == 0 ) printf("fork() 1, (pid:%d)\n", rc); el...
2019-04-12 20:56:20
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原创 Python语言程序设计（北京理工大学）第九周_Python Programming week09
数据分析：Numpy: 表达N维数组的最基础库Pandas: Python数据分析高层次应用库SciPy: 数学、科学和工程计算功能库数据可视化：Matplotlib: 高质量的二维数据可视化功能库Seaborn: 统计类数据可视化功能库Mayavi：三维科学数据可视化功能库文本处理：PyPDF2：用来处理pdf文件的工具集NLTK：自然语言文本处理第三方库Pyth...
2019-01-31 13:43:58
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原创 Python语言程序设计（北京理工大学）第八周_Python Programming week08
1. 自顶向下设计主要由下列哪个语法元素实现？A. 函数B. 过程C. 对象D. 循环结构函数是自顶向下设计的关键元素，通过定义函数及其参数逐层开展程序设计。2. 关于计算思维，以下选项描述正确的是...
2019-01-31 12:07:40
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原创 Python语言程序设计（北京理工大学）第七周_Python Programming week07
1. 以下选项对文件描述错误的是：A. 文件是数据的集合和抽象B. 文件可以包含任何内容C. 文件是程序的集合和抽象D. 文件是存储在辅助存储器上的数据序列函数或类是程序的集合和抽象，文件不是。2....
2019-01-31 00:04:32
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原创 Python语言程序设计（北京理工大学）第六周_Python Programming week06
1. 关于Python组合数据类型，以下描述错误的是：A. 序列类型是二维元素向量，元素之间存在先后关系，通过序号访问B. 组合数据类型可以分为3类：序列类型、集合类型和映射类型C. 组合数据类型能够将多...
2019-01-29 23:18:05
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原创 Python语言程序设计（北京理工大学）第五周_Python Programming week05
1. 以下关于递归函数基例的说法错误的是：A. 每个递归函数都只能有一个基例B.递归函数的基例决定递归的深度C. 递归函数的基例不再进行递归D. 递归函数必须有基例每个递归函数至少存在一个基例，但可能存在多个基例。2. 以下选项不是函数作用的是：A. 复用代码B. 降低编程复杂度C. 提高代码执行速度D. 增强代码可读性函数不能直接提高代码执行速度。...
2019-01-29 17:17:30
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原创 Python语言程序设计（北京理工大学）第四周_Python Programming week04
整数的加减和描述编写程序计算如下数列的值：1-2+3-4...966...
2019-01-28 17:55:52
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原创 Python语言程序设计（北京理工大学）第三周_Python Programming week03
实例3：天天向上的力量描述这是"实例"题，与课上讲解实例相同，请作答检验学习效果。工作日模式要努力到什么水平，才能与每天努力1%一样？...
2019-01-27 18:29:42
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原创 OS note03 -- clone
references:https://blog.csdn.net/gatieme/article/details/51417488 Linux中fork，vfork和clone详解（区别与联系）int clone(int (fn)(void ), void *child_stack, int flags, void *arg);fn是函数指针，这个就是指向程序的指针，就是所谓的“剧...
2019-01-27 00:17:01
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原创 Python语言程序设计（北京理工大学）第二周_Python Programming week02
实例2: Python蟒蛇绘制描述这是"实例"题，与课上讲解实例相同，请作答检验学习效果。使用turtle库，绘制一个蟒蛇形状的图形。...
2019-01-26 23:49:21
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原创 Python语言程序设计（北京理工大学）第一周_Python Programming week01
货币转换 I描述人民币和美元是世界上通用的两种货币之一，写一个程序进行货币间币值转换，其中：人民币和美元间汇率固定为：1美元 = 6.78人民币。程序可以接受人民币或美元输入，转换为美元或人民币输出。人民币采用RMB表示，美元USD表示，符号和数值之间没有空格。...
2019-01-26 21:24:41
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原创 计算理论Computing Theory_Chapter01
Setelements/memberssingleton: (one element)empty setproper setunionintersectiondifference:Idempotency, Commutativity, Associativity, Distributivity, Absorption, DeMorgan's laws:disj...
2019-01-23 17:30:32
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原创 OS -- three easy pieces -- (Persistence 01) I/O Devices
Persistence:making information persist, despite computer crashes, disk failures, or power outages. I/O Devicesintroduce the concept of an input/output (I/O) device and show how the operating s...
2019-01-16 09:32:12
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原创 OS -- three easy pieces -- Introduction
Virtualization:Assume there is one physical CPU in a system (though now there are often two or four or more). What virtualization does is take that single (physical) CPU and make it look like many...
2019-01-15 19:42:39
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原创 第九周 标准模板库STL(二) - PKU[课程作业]程序设计与算法（三）C++面向对象程序设计_C++ Object Oriented Programming week09
1:Set#include<iostream>#include<set>#include<string>using namespace std;int main(){ int n; cin >> n; multiset<int> ms; set<int> s; multiset<int>:...
2018-05-23 19:08:57
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