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"HTML" "Theoretical learning" 1. Basic theory

" To set video continuous playbackpreload = "preload" preload, this property is invalid when AutoPlay is usedAudio: Audio properties: Audio has properties similar to video--autoplay, controls, loops, preloadHTML New input type:Other elements: Hgroup: Used to group the title of a chunk of content across a page or pageFigure: Represents a separate stream content that typically represents a single unit in the document contentFiguration: Adding a caption to a figure element(Stream: Elements used in

The absurd theory of the so-called "poor learning management, technology for the rich"

Managing computers is like managing peopleThe meaning of human existence is to do things, but a person can do things is limited, so there are more people together to do common things, but because people are unstable, if not to limit, will be wrong, so the manager was born, and the manager, first of all, he will do things, to qualify as a manager, Arranging other people to do things for themselves, become managers, what to do is to communicate with others, in this way to let others replace their

The probability theory of machine learning preparatory knowledge (bottom)

to approximate a two-item distribution when the number of experiments is very large, or to approximate the Poisson distribution at high average incidence, and also to the large number theorem. The Gaussian distribution is determined by two parameters: the desired μ and variance σ2, with the following formula:As an example of a Gaussian distribution, it is known from this graph that the desired decision determines the central position of the normal curve, and the variance determines the steep or

Machine Learning Theory and Practice (13) probability graph model 01

01 Brief Introduction The probability graph model is the product of the combination of graph theory and probability theory. It was created by Judea Pearl, a famous one. I like the probability graph model tool very much, it is a powerful multi-variable and visualized modeling tool for variable relations, mainly including two major directions: undirected graph model and directed graph model. An undirected gra

ACM Learning process-hdu5407 CRB and candies (number theory)

can divide n+1 maximum number of times).That is, the product of all P^maxn divided by the product of p^K, the numerator equals [1, 2, 3,.... n+1], and the denominator equals n+1. The result is consistent with the conclusion of the puzzle.Prove the process a little rubbing ....If K and maxn are found in order, the complexity is O (Num*log (p)), where num is the number of primes ,P is the prime number. If two points are found, O (Num*log (LOGP))Code: O (Num*log (p))#include #include#include#inclu

ACM learning process-snnuoj1132 remainder sum (number theory)

] =x2; } Else{ up=0; X.val[i+J] =X1; } } if(Up! =0) X.val[i+J] =Up ; } X.len= i +J; while(x.val[x.len-1] ==0 X.len >1) X.len--; returnx; } bignumoperator/(Const inta)Const{bignum x; intDown =0; for(inti = len-1; I >=0; --i) {X.val[i]= (val[i]+down*unit)/A; down= Val[i] + down*unit-x.val[i]*A; } X.len=Len; while(x.val[x.len-1] ==0 X.len >1) X.len--; returnx; } LLoperator%(ConstLL a)Const{LL x=0; for(inti = len-1; I >=0; --i) x= ((X*unit)%a+val[i])%A; retur

ACM Learning process-bzoj2956 modulus and (number theory)

#includestring>#defineLL Long Long#defineMOD 19940417#defineNsix 3323403using namespacestd;intN, M; LL Cal (intLenintx) {LL ans=0, TMP; intJ; for(inti =1; I i) {j= min (len, x/(x/i));//This sentence doesn't have to be min,j to cross .TMP = ((LL) i+j) * (j-i+1)/2%MOD; Ans+ = tmp* (x/i)%MOD; Ans%=MOD; I=J; } returnans;} inline ll sum (ll x) {returnx* (x+1)%mod* (2*x+1)%mod*nsix%MOD;} LL Cal2 (intXinty) {LL ans=0, TMP, ttmp; intJ; for(inti =1; I i) {j= Min (x/(x/i), y/(y/i)); //j = min (j, x);

Hadoop learning notes ----- hbase Theory

length Common Client time queries "the latest data from a certain time point" or "giving me all versions of Data" The element is determined by the row key, column family qualifier, and unique timestamp; The elements are stored in bytecode, and there are no types; Hbase physical model: 650) This. width = 650; "Title =" hbase.png "src =" http://s3.51cto.com/wyfs02/M01/48/66/wKioL1QHVYKzK1M7AAIcMsaxpOo869.jpg "alt =" wkiol1qhvykzk1m7aaicmsaxpoo869.jpg "/> This article from "Li

Android Learning Note (14) Handler theory supplement

First, how to download Android source codeIn SDK Manager, select the sources for Android SDK.Ii. Preliminary introduction of Threadlocal1) Executes the set (Object obj) method of the ThreadLocal object (static final ThreadLocal sthreadlocal) and stores a key-value pair with the current thread as the key.2) Execute the Get () method of the Threadlocal object, and the corresponding value will be fetched according to the current thread object as the key.In the Looper method call that was mentioned

Shell theory Learning (II.)

to manipulate various commands, and script will faithfully record all output information. If you want to end the operation, exit script [Emailprotected]~]#script/tmp/test.txtscriptstarted,fileis/tmp /test.txt[[emailprotected]~]#ls/tmp/test.txt/tmp/test.txt[[emailprotected] ~]#{cattest.txt;find/root/test/-name "*.txt";d ate+%f;} hellomyworld! thisisazhuijia!/root/test/file5.txt/root/test/file2.txt/root/test/file4.txt/root/test/ file3.txt2015-01-09[[emailprotected]~]#find/root/test/-name "*.txt"

Java NiO non-blocking theory learning

key=(Selectionkey) ite.next (); //Remove the selected key to prevent duplicate processingIte.remove (); //Connection event occurs if(Key.isconnectable ()) {Socketchannel channel=(Socketchannel) key. Channel (); //If you are connecting, complete the connection if(Channel.isconnectionpending ()) {channel.finishconnect (); } //set as non-blockingChannel.configureblocking (false); //here, you can send messages to the server.Channel.write (Bytebuf

Multi-threaded Learning-Basics (v) The difference between sleep () and yield () (theory)

", he gives the opportunity to other priority threads, if there is only the current thread and a lower than the current thread execution priority of the thread, then the current thread will still take precedence.It is important to note that the priority here is simply the amount of opportunity to execute, and does not mean that the priority thread must be enters upgradeable to the CPU than the lower-priority line. Just the probability of execution.(5) Sleep () allows a lower-priority thread to g

Reading Notes for statistical learning theory

Let's continue the discussion of reading Vapnik ' s book Statistical Learning theory. In the very beginning of the book, Vapnik first described and the fundamental approaches in pattern recognition:the Parametri C Estimation approach and the non-parametric estimation approach. Before introducing the non-parametric approach, which the support vector machine belongs to, Vapnik first address the Foll Owing thr

Information Theory Learning

Information Theory and codingInformation Theory and coding1. IntroductionBased on probability theory, pay attention to concept understanding, not excessive pursuit of mathematical deductionFounder of Information Theory (C.e.shannon) Shannon, American scientist, published the Mathematical

Machine Learning Theory and Practice (4) logical Regression

From this section, I started to go to "regular" machine learning. The reason is "regular" because it starts to establish a value function (cost function) and then optimizes the value function to obtain the weight, then test and verify. This entire process is an essential part of machine learning. The topic to learn today is logical regression, which is also a supervised

Knowledge part of machine learning theory--deviation variance balance (bias-variance tradeoff)

easier to solve, such as increasing the complexity of the model (increasing the branches in the decision tree, increasing the number of training in the neural network, etc.), increasing the features ("Combination", "generalization", "correlation"), and reducing the regularization factor (reference).Over fitting: The solution of overfitting usually has to re- clean the data (which causes the overfitting to be caused by the data impure), increases the sample size, reduces the model complexity, us

JavaScript Theory Learning method

Self-learning JS since the sense of JS knowledge point too much, although to know, blog Park, CSDN and other platforms to see a lot of articles how to learn JS, but as a novice how to reason is not clear thinking how to learn. Learning JS Almost half a year to learn two ways to learn, the first method: to find a platform to record their own learning every point o

CSS Learning (12)-text linefeed Theory and Practice

CSS Learning (12)-text linefeed Theory and PracticeI. theory:1. word-wrap:A. normal performs line breaks in spaces or hyphensB. break-word does not cut off the line feed of English Words2. word-break:A. normal Chinese to boundary Chinese character line feed, English from the entire word line feedB. break-all forcibly truncate the line feed of English WordsC. keep

Small Ant Learning Sphinx (1)--theory Chapter

On-line video on the Php+mysql+sphinx, before just heard, thought today finally able to learn a rise and gain insight, one hours of theoretical discourse finished, and did not anticipate the kind of knowledge to absorb a lot of satisfaction, one theory more, and secondly are in the operation of Linux, no way to practice , first write today's small notes, and then slowly delve into this piece of content.Sphinx generates index data and provides a more s

Domain model of field-driven design theory learning notes

has better maintainability.The domain model runs through the whole process of software requirement analysis, design and development, and becomes the core link of communication between all members of a team, and everyone is facing the same model. The old idea that the demand for personnel to develop requirements specifications, designers research requirements specifications to write design books, developers based on the design of the book to write code. Domain-driven design obviously does not re

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