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[MOOC Notes] Chapter 1 Introduction (data structure)

, Are equivalent toBasic commands. In the progressive sense, the two are roughly the same. The main method for complexity analysis: 1. iteration: Sum of Series 2. recursion: recursive tracking + recursive equation 3. Prediction + Verification Level complexity: Arithmetic series Same level as last square Power Series Level 1 higher than power Geometric Series Same level as last Convergence level O (1) Geometric Distribution O (1)

JavaScript data type and type detection functions-MOOC ArraysSimilar programming exercises

JavaScript data type and type detection functions-MOOC ArraysSimilar programming exercisesBasic Type stringNumberBooleanFunctionUndefinedObject (null, Array, Date, window) implicit conversion with "=" num-string var str = num + ''string-num var num = str-0"=" For implicit conversion and determination (that is, to determine the value in the variable)"=" Directly determines (whether it is a thing) (NaN! = NaN

[MOOC notes] Chapter III list (data structure)

the tail node while (next = NODE.GETSUCC ())! = This.trailer) {//delete each of the same nodes if (Node.getdate (). Equals (Next.getdate ())) {This.remove (next);} else {node = next;}} Returns the scale change amount of return oldsize-this.size;}But because lists are seek location access rather than rank-and-seek access, an ordered list does not produce more efficiency in the lookup. Therefore, the lookup time complexity of the sequence table is the same as the normal list O (n).Note: This less

Chinese University mooc-Chen, He Chinming-Data structure basic problem sets 03-1. Two-part method for finding the polynomial single

, giving the interval endpoints a and B sequentially in line 2nd. The topic guarantees that the polynomial has a unique single root within a given interval. output format: Outputs the root of the polynomial within the range in a row, exactly 2 digits after the decimal point. Input Sample: 3-1-3 1-0.5 0.5 Output example: 0.33 Chinese University mooc-Chen, He Chinming-Data structure basic pr

Chinese University mooc-data Structure basic problem sets, 07-1, sorting

title Link:http://www.patest.cn/contests/mooc-ds/07-1Title Analysis: This two parts in the test of various different sorting algorithms in various data situations performance. Therefore there is no standard answer. The purpose of this post is to give the C + + implementation form of various sorting algorithms, and compare and summarize the results. Hope to bring you help . Code for various sorting algorithm

Data mining,machine learning,ai,data science,data science,business Analytics

What is the difference between data Mining (mining), machine learning (learning), and artificial intelligence (AI)? What is the relationship between data science and business Analytics? Originally I thought there was no need to explain the problem, in the End data Mining (mining), machine learning (machines le

Use SharePreferences to access data (MOOC notes), sharepreferences

Use SharePreferences to access data (MOOC notes), sharepreferences 0. video address: http://www.imooc.com/video/3265 1. Use SharePreferences to access data: Public class MainActivity extends Activity {@ Override protected void onCreate (Bundle savedInstanceState) {super. onCreate (savedInstanceState); setContentView (R. layout. activity_main); SharedPreferences p

Log on to the instance and save the data (use SharedPreferences to save the user name for MOOC notes ).

Log on to the instance and save the data (use SharedPreferences to save the user name for MOOC notes ). Take notes when you perform operations after learning the video. 0. video address: http://www.imooc.com/video/3265 1. Function preview: Note: 1) enter the wrong user name and password and click log on. A prompt box is displayed, indicating "Logon prohibited "; 2) enter the correct user name and password,

China University mooc-Chen, He Chinming-data structure-2015 Autumn 02-LINEAR structure 1

The product and sum of the two unary polynomials are obtained by the design function respectively.Input format:Input is divided into 2 lines, each line is given the number of non-0 polynomial, and then the exponential degradation way to enter a polynomial non-0 coefficients and exponents (absolute value is not more than 1000 integers). The numbers are separated by a space.Output format:The output is divided into 2 rows, and the coefficients and exponents of the product polynomial and the polynom

[MOOC Notes] sorting topics (data structure)

ordering.3. Merge sortIdea: Divide the whole sequence into multiple sub-sequences, sequence the subsequence sequentially, and finally merge into an ordered sequence, with the following algorithm:/** * Merge sort, time complexity O (NLOGN) * @param arr array to sort * @param the starting position of the lo to sort interval * @param hi to the end of the sort interval */public static void MergeSort ( Int[] arr, int lo, int hi) {//If there is only one element left in the interval, the recursive if

Data science Study Notes 1. science Study Notes

Data science Study Notes 1. science Study Notes Mutiple Plots on One Graphplt.plot(x, norm.pdf(x))plt.plot(x, norm.pdf(x, 1.0, 0.2)) #1.0 = mean, 0.2 = DSplt.show() Use plt. savefig to save the image as blank: Solution: Call plt. savefig before plt. show (). Scatter Plot From pylab import randnX = randn (10000) Y = randn (10000) plt. scatter (X, Y) # Pay Attentio

Algorithms and data structures: Computing Science

Algorithms and data structures: Computing Science Excerpt from: algorithms and data structures: the Science of Computing By Douglas Baldwin and Greg W. scragg Translated by Liu Jianwen (http://blog.csdn.net/keminlau ) Charles River media 2004 (640 pages) ISBN: 1584502509Back Cover While computing

Comprehensive learning path–data Science in Python deep learning path-Learn with Python data

http://blog.csdn.net/pipisorry/article/details/44245575A very good article on how to learn python and use Python for data science, data analysis, machine learning Comprehensive learning Path–data Science in PythonDeep learning paths-da

[Data Science] extract data from text, JSON files

Text files are basic file types, whether CSV, XLS, JSON, XML, and so on, can be read as text files.#-*-coding:utf-8-*-Fpath ="Data/textfile.txt"F= Open (Fpath,'R')## Read characters by characterFirst_char = F.read (1)Print "First Char:", First_char## Change the location of the file object, the location is calculated according to ByteSize## If you don't move the position to the beginning, then the reading starts at the current position.f.seek (0)## Rea

Johns Hopkins University series of data Science courses--r language: Data types

valuesIs.na () is used to test whether the object is Na,is.nan () to test whether the object is Nan. Na is Nan, but Nan is not na,nan much deeper than NA.10. Data frameThe data frame is used to store tabular data and is created with Data.frame (). You can treat a data frame as a special list collection, with the same

One Facts about the Data science which you must know

One Facts about the Data science which you must knowStatistics, machine learning, Data science, or analytics–whatever-call it, this discipline was on rise in the last Quarte R of Century primarily owing to increasing data collection abilities and exponential increase in comp

Data Science Blogs

Data Science BlogsA curated list of data science blogs Agile Data Science http://blog.sense.io/(RSS) Airbnb Data Blog http://nerds.airbnb.com/

R VS Python in Data science: The winner is ...

R VS Python in Data science: The winner is ...In the "Best" data Science tools game, R and Python have their own pros and cons. The choice between the two depends on the use of the background, the need to learn spending and other tools that are often usedMartijn Theuwissen published in Datacamp.At Datacamp, students of

Wuyi Free Data Science Books

Wuyi Free Data Science BooksA great collection of free data science books covering a wide range of topics from data science, business Analytics, data Mining and Big

Data Science from Scratch's MapReduce

MapreduceMapReduce is a computational model, except that the computational model is in the world of parallel computing.Consider a simple example-word statisticsfrom collections import Counterimport redocuments = ["data science", "big data", "science fiction"]def tokenize(message): message = message.lower() all_wo

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