machine learning exercises

"The users total was $I the bash is $J"ExitWrite a script:1, add 10 users user1 to User10, password with the user name, but requires only the user does not exist in the case can be added;Extended:Accept a parameter:Add: Adding User user1. User10Del: Delete User user1. User10Other: ExitAdminusers User1,user2,user3,hello,hi!/bin/bashif [= = = "Add"];thenFor I in {1..10};d oIf ID user$i >/dev/null;thenecho "user$i is exist"ElseUseradd user$iecho "User$1" | passwd--stdin user$i >/dev/nullFiDoneelif

":" '/\[916\]/{print $ ' datafile8. Show Mike's donation. Each value is displayed with a $ start. such as $250$100$175Awk-f ":" '/^mike/{print "$" $ "$" $ "$" $4 "$" $ $ "datafile9. Display last name followed by a comma and name, such as Jody,savageAwk-f ":" ' {print $} ' datafile | awk ' {print $, ', ', ' $ '10. Write an awk script that functions as:Displays the full name and phone number of the savage.. Show donations for ChetThe names of all the first one-month donations are displayed.Note:

> B? (A > C?) (A > d? a:d): (C > d? c:d)): (b > C?) (b > d? b:d): C > d? C:D);111 printf ("%d", max); the */113 theSystem"Pause"); the return 0; the}The above are some of the code you practice is mostly familiar with the use of the IF else nested switch statement using the trinocular operatorIt is important to note that the scanf function cannot be changed to scanf_s in vs2013 .In addition, the use of GetChar (), when there will be a flash-back situationCan be replaced by system ("pause");

) + Pow (int (s[1]), 3) + POW (int (s[2]), 3) = = I:print (i, end= ",") Answer3 () def answer4 (): "" "The collar uses the Divmod function to calculate : Return: "" " Print ("\ n Output four", end= ":") for I in range (+): M = i sumnum = 0 while m > 0: M, n = Divmod (M, ten) Sumnum + = n * * 3 if Sumnum = = I:print (i, end= ",") Answer4 () def answer5 ( ): "" is implemented using the list for if usage: return: "" "Print (" \ n Output five ", end=": ") L = [I for I in range (+) if (I//1 * *

"" "Title: Output 9*9 multiplication table. "" "Def Answer1 ():" " in the most common double loop to output : return:" "" print ("Output One:") for I in range (1): For j in range (1, i + 1): print ("%d x%d =%2s"% (i, J, I * j), end= " ") print () answer1 () def answer2 (): The "" " while loop, with another formatting note for print percent (%) formatted output, sets the output format for the flag with%, and the fomate format is formatted with a colo

Form ExerciseRegistration Information Form　　Brother Lian Learning python----form production exercises

patients are waiting in line! ") \ n ") else:print (" \ n currently queued patient: ") for I in List[::-1]: print (i,end=") Print ("\ n") elif score = = 4:if len (list) = = 0:print ("No patients are waiting in line!") \ n ") else:print (" \ n all queued patients no longer queued: ") for I in List[::-1]: print (i,e Nd= ") list.clear () print("\ n") exit () Elif score ==5:if len (list) = = 0:print ("There is no patient, happy work!") \ n ") Else:print (" The doctor will come back from

]=temp; } } } } Public Static voidPrintArray (int[] arr) {System.out.print ("["); for(inti = 0; I ){ if(i = = Arr.length-1) {System.out.println (Arr[i]+"]"); }Else{System.out.print (Arr[i]+","); } } }}7. Bubble Sort: Public classarraytest{ Public Static voidMain (string[] args) {int[] arr = {3,1,5,7,8,9,2}; Bubblesort (arr); PrintArray (arr); } Public Static voidBubblesort (int[] arr) { for(inti = 0; i){ for(intj =

output four: ") a = [[1, 2], [3, 4]] B = a[:] Validate (A, B) answer4 () def ANSWER5 (): "" "Deep copy Copy.deepcopy:return:" "" Print ("\ n output five:") a = [[1, 2], [3, 4]] B = Copy.dee Pcopy (a) validate (a, B) Answer5 () def ANSWER6 (): "" "Shallow copy copy.copy, with Answer3:return:" "" Print ("\ n output six:") A = [[1, 2], [3, 4]] B = copy.copy (a) validate (a, B) Answer6 () def answer7 (): "" "Use list generation using a list of for processing, as if the generator : Return: ""

%16 and! Year%25 these are not leap years, and vice versa! (year%4 or year%16 and!) YEAR%25) converts a bitwise operation for a leap year! (Year3 or year15 and!) (year%25)):p Aram T:: Return: "" "Print (" Calculate Nine ", end=": ") days = [31, 28, 31, 30, 31, 30, 31, 31, 30, 31, 30, Year = T.year if Not (year 3 or Year 15 (year)): days[1] = print (sum (days[0:t.month-1) + t.day) def answer (): "" "to determine the date entered by a try Whether it is correct: return: "" "Year = input (" Enter

Label:After the first chapter of the basic data operation instructions are practiced, some operations of the database are performed. Create a table class has two columns: numbers and names: CREATE table Class (numbers number, names char (20));This is the name of the case, don't want to add "" "double quotation mark numbers this is the column, number this is the data type2. When you are building a table, limit which data can be storedCREATE table Class2 (numbers number not NULL, names cha

another, or 8 seconds to exit. #d. Next, set the password for the user, first prompt the user to enter the password to be set, the password input process is not visible #e. Length detection of the password entered by the user in the previous step, if less than 5 bits (including 5-bit), prompt the user password is too short, and exit # F. For complexity detection of the password entered by the user in step D, if the input is exactly the same as a line entry in the/usr/share/dict/words dictionary

I. Working methods of machine learning ① Select data: Divide your data into three groups: training data, validating data, and testing data ② model data: Using training data to build models using related features ③ validation Model: Using your validation data to access your model ④ Test Model: Use your test data to check the performance of the validated model ⑤ Use model: Use fully trained models to mak

This article compiles a number of frameworks, libraries, and software (sorted by programming language) for the machine learning domain.1. c++1.1 Computer Vision ccv-based on C language/provide cache/core machine Vision Library, novel Machine Vision Library opencv-it provides C + +, C, Python, Java and MATL

Octave Machine Learning Common commands A, Basic operations and moving data around 1. Attach the next line of output with SHIFT + RETURN in command line mode 2. The length command returns a higher one-dimensional dimension when apply to the matrix 3. Help + command is a brief aid for displaying commands 4. doc + command is a detailed help document for displaying commands 5. Who command displays all current

This paper is organized from the "machine learning combat" and Http://write.blog.csdn.net/posteditBasic Principles of Mathematics: Very simply, the Bayes formula: Base of thought: For an object to be sorted x, the probability that the thing belongs to each category Y1,y2, which is the most probability, think that the thing belongs to which category.Algorithm process: 1. Suppose something to be sorted x, it

Tags: virtual machine installation Connect to the Linux virtual machine learning environment Build-Virtual machine Create "click" to open this virtual machine, enter the system installation interface.650) this.width=650; "Src=" Https://s1.51cto.com/oss/201711/17/0f55f83d

: , where θ is the vector of (n+1) x1, x is the vector of (n+1) x1, ∙. We all use vectors to represent the hyper-plane behind. Except that θ is called a weight, and b is biased, so the complete expression of the super plane is:θ*x+b=0 The Perceptron model can be defined as y=sign (θ∙x+b) where: If we call sign the activation function, the difference between the perceptual machine and the logistic regression is that the sign,logistic regression acti

Brief introduction:Support Vector Machine (SVM) is a supervised learning model of two classification, and his basic model is a linear model that defines the largest interval in the feature space. The difference between him and the Perceptron is that the perceptron simply finds the hyper-plane that can divide the data correctly, and SVM needs to find the most spaced hyper-plane to divide the data. So the per

Support Vector MachineSVM (Support vector Machines,svms) is a two-class classification model. Its basic model is a linear classifier that defines the largest interval in the feature space, which distinguishes it from the perceptual machine, and the support vector machine also includes the kernel technique, which makes it a substantial nonlinear classifier. The learning