machine learning exercises

Topic题目标题：计算阶乘n!是一件可怕的事情，因为当n并不是很大时，n!将是一个很大的值。例如13! = 6227020800，已经超过了我们常用的unsigned int类型的取值范围。请设计一个程序，使其可以计算100以内的数的阶乘，结果用字符串的形式输出详细描述：接口说明原型：void CalcNN(int n, char *pOut)输入参数：int n 需要计算的阶乘数输出参数：char *pOut 结算结果，内存由调用者负责管理返回值：无限制：无举例：题目来源: 软件训练营 练习阶段: Code/* ---------------------------------------* Date: 2015-06-30* sjf0115* title: Horrible factorial * Source: Huawei on-Machine-------------------------- ---------------*/#include #include #incl

) { vectorstring>ResultintSize = Intrain.size ();if(Size 0) {result; }//ifHelper (Intrain,result,0); Sort (Result.begin (), Result.end ());returnResult;}intMain () {intN//freopen ("C:\\users\\administrator\\desktop\\c++.txt", "R", stdin); while(Cin>>n) {stringTrain"");intNum for(inti =1; I Cin>>num; Train + = num +' 0 '; }//for vectorstring>Trainnum = Trainleft (train);//Output intSize = Trainnum.size (); for(inti =0; i intCount = Trainnum[i].size (); for(intj =0; J if(J = =0)

This column (Machine learning) includes single parameter linear regression, multiple parameter linear regression, Octave Tutorial, Logistic regression, regularization, neural network, machine learning system design, SVM (Support vector machines Support vector machine), clust

[Huawei machine trial exercise questions] 15. Delete duplicate characters/delete duplicate strings, Huawei exercises Question Title: delete duplicate characters. Given a string, remove all redundant characters in the string that have already been duplicated. Keep the remaining characters and output the processed string. Ensure the order in which the characters appear and are case sensitive. Description: in

TopicDescribe:有n个人围成一圈，顺序排号。从第一个人开始报数（从1到3报数），凡报到3的人退出，问最后留下的那位是原来第几号。Topic Category: 数组,指针 Difficulty: 初级 Run time limit:Memory Limit:Stage:入职前练习 Input:使用标准输入stdio.多行，每行一组数据。Output:多行，每行对应求和结果。Sample input:3Sample output:2Code/* ---------------------------------------* Date: 2015-07-01* sjf0115* title: Count off * Source: Huawei----------------------------- ------------*/#include #include using namespace STD;intCircleout (intNintm) {if(N 0){return-1; }//if listint>Circle//Initial numberi

Oledb.oledbdataadapter = New oledb.oledbdataadapter (strSQL, connconnection) Myadapter.fill (myDataSet, "Accountact") connconnection.close () ' pulls data out of the dataset to display on the control () Datagridview1.datasource = mydataset.tables (0) Datagridview1.autosizecolumnsmode = Datagridviewautosizecolumnsmode.allcells View all user accounts ' Connect database Dim Con As String = ' Provider=Microsoft.Jet.OLEDB.4.0;Data source= atm.mdb ' Di

and neuroscience (and many other fields). With lots of the open problems and opportunities for fundamental I'll be seeing multiple reinforcement Learn ing breakthroughs in the coming years. And what could be more fun than teaching machines to play StarCraft and Doom? How to Study reinforcement Learning There are many excellent reinforcement Learning resources out There. Two I recommend the most are:david

What is machine learning?"Machine learning" is one of the core research fields of artificial intelligence, its initial research motive is to let the computer system have human learning ability to realize artificial intelligence.In fact, since "experience" is mainly in the fo

Tags: A * font a work put weight varchar length differentFunction:1.Function View string contains several special characters, such as ' A**B*CEDF ' contains several ' * '2.function to concatenate different work in the employee table into a string3.function calculates personal income tax, salary, salary income minus 3500,Tax-free rate (%) rate divisorNo more than 1500 3 0Over 1500 to 4500 10 105Over 4500 to 9000 20 555Over 9000 to 35000 25 1005--1Create or Replace functionSpecial_char (cinch varc

properly handle the training data and problems.Remember in the last lecture we have introduced the definitions and differences between bias and variance, and here we look at the environment in which they are produced:Bias:j (train) Large, J (CV) Large, J (train) ≈j (CV), bias produced in D small, underfit stage;Variance:j (train) Small, J (CV) Large, J (train) Want to ensure that bias small, it is necessary to ensure that there are enough feature, that linear/logistics regression ther

Objective Machine learning is divided into: supervised learning, unsupervised learning, semi-supervised learning (can also be used Hinton said reinforcement learning) and so on. Here, the main understanding of supervision and unsu

and neuroscience (and many other fields). With lots of the open problems and opportunities for fundamental I'll be seeing multiple reinforcement Learn ing breakthroughs in the coming years. And what could be more fun than teaching machines to play StarCraft and Doom? How to Study reinforcement Learning There are many excellent reinforcement Learning resources out There. Two I recommend the most are:david

sixth week. Design of learning curve and machine learning system Learning Curve and machine learning System Design Key Words Learning curve, deviation variance diagnosis method, error a

In machine learning-Hangyuan Li-The Perceptual Machine for learning notes (1) We already know the modeling of perceptron and its geometrical meaning. The relevant derivation is also explicitly deduced. Have a mathematical model. We are going to calculate the model.The purpose of perceptual

Today I saw in this article how to choose the model, feel very good, write here alone.More machine learning combat can read this article: http://www.cnblogs.com/charlesblc/p/6159187.htmlIn addition to the difference between machine learning and data mining,Refer to this article: https://www.zhihu.com/question/30557267D

Learning notes for "Machine Learning Practice": Implementation of k-Nearest Neighbor algorithms, and "Machine Learning Practice" k- The main learning and research tasks of the last semester were pattern recognition, signal theor

Machine learning and its application 2013 content introduction BooksComputer BooksMachine learning is a very important area of research in computer science and artificial intelligence. In recent years, machine learning has not only been a great skill in many fields of comput

For the performance of four different algorithms in different size data, it can be seen that with the increase of data volume, the performance of the algorithm tends to be close. That is, no matter how bad the algorithm, the amount of data is very large, the algorithm can perform well.When the amount of data is large, the learning algorithm behaves better:Using a larger set of training (which means that it is impossible to fit), the variance will be l

Original: Image classification in 5 Methodshttps://medium.com/towards-data-science/image-classification-in-5-methods-83742aeb3645 Image classification, as the name suggests, is an input image, output to the image content classification of the problem. It is the core of computer vision, which is widely used in practice. The traditional method of image classification is feature description and detection, such traditional methods may be effective for some simple image classification, but the tradit

Learning notes for "Machine Learning Practice": two application scenarios of k-Nearest Neighbor algorithms, and "Machine Learning Practice" k- After learning the implementation of the k-Nearest Neighbor Algorithm, I tested the k-