Data mining and big data analysis
the three main trends of adventure and mining are as follows:
first King flow: high first attack, high king as the sign; Defense and dodge are very low, with critical hit skill as the main skill
recovery flow: high defense and high dodge are the main characteristics of this school. The first attack is generally low, with blood adding skill as the main skill
defense flow: high defense and high king, with pure attack skill as the main skill
there are some cold schools represented by weak flow, but the strength of this school is low, It's easy to be taken away by the first king stream, or killed by the backhand of the defending King stream, or dragged to death by the restoring stream, so it's rare
Mining is a nickname for the exploration method of acquiring bitcoin. Because of its working principle is very similar to mining minerals, so named. In addition, bitcoin explorers who do mining work are also known as miners
bitcoin network generates new bitcoin through "mining". In essence, the so-called "mining" is to use computers to solve a complex mathematical problem to ensure the consistency of bitcoin network distributed accounting system
bitcoin network will automatically adjust the difficulty of mathematical problems, so that the whole network can get a qualified answer about every 10 minutes
then the bitcoin network will generate a certain amount of bitcoin as a reward to reward the person who gets the answer
extended data:
to be a miner, just "mine" bitcoin and search for 64 bit numbers by computer. By repeatedly decrypting with a computer, it competes with other gold miners to provide the number needed for the bitcoin network
if the computer can successfully create a set of numbers, it will get 25 bitcoins. Bitcoin is decentralized. It needs to create a fixed number of bitcoins per unit of computing time. It can get 25 bitcoins every 10 minutes
by 2140, the upper limit of bitcoin in circulation will reach 21 million. In other words, bitcoin system can be self-sufficient, which can be translated into coding to resist inflation and prevent others from sabotaging< br />
It's a scam. Many Internet enterprises and network security enterprises believe that illegal "mining" has become a serious network security problem
with the rise of "cloud mining", the virtual machine has become the main use object of digital currency such as Monroe coin and Eli coin, and the situation of embezzling cloud computing resources for "mining" has also increased significantly; Security team monitoring found that "competing for mining machine" has become one of the important purposes of Botnet expansion; And found a new type of "mining" virus (mining XmR / Monroe), the virus spread wildly in two months, illegal "mining" profits of nearly one million yuan
extended information:
from a commercial point of view, the business model of mining can walk out of a "healthy road". As long as the "incentive money" is lower than the average cost of new users in the market, the business model will be reasonable and feasible
however, if the platform tempts users to participate with "no capital, no profit", it is worth being vigilant. The so-called "mining" opportunity provided by the platform is likely to be "digging a good hole" waiting for you to jump in
but I still hope it can last forever...
you're very powerful... I just read the title and was shocked...
I'm still thinking about how monkeys can mine...
it's so interesting
please refer to http://bbs.polchina.com.cn/viewthread.php?tid=251129&extra=page%3D1
for example, in medical application, we study heart disease and want to know what patients can do to be healthier, so we collect big data. But all kinds of data proced by a person every day are massive. A large amount of data has nothing to do with pathological reactions in essence. If you collect and analyze them, you will not only do useless work, but also draw wrong conclusions. A negative case is that in the casinos of Las Vegas in the United States, the red and black turntables use a large screen to display the previous lottery information. Many people bet "black" when they see "red" appearing more often in front of them. This is a typical "data noise" -- as statisticians all know, this is completely random, and these so-called "big data" are invalid or even interfering
"to carry out big data analysis, we must have 'application scenarios'. We must stress the accuracy and relevance of data, and the' big 'or' small 'of data itself is not the key." Ling Xiaofeng said that the blind pursuit of big data can not proce "useful results", on the contrary, it is easy to "self confusion", which is also a common misunderstanding in the current big data instry
this view has a strong practical pertinence. At present, many manufacturing enterprises will call it "big data". No matter what procts they are engaged in, they are all connected with optical fiber. With sensors, they proce a lot of "data" all the time. The problem is that when the data is available, it is impossible to tell which is effective and which is invalid. It not only causes the waste of hardware equipment and statistical computing resources, but also draws wrong conclusions e to the interference of "data noise", which weakens the market competitiveness
"we call big and useless data 'low value density' Tan Jianrong, academician of the Chinese Academy of engineering, told reporters that in the past, the technical terms were "data mining" and "data analysis". Now why should we prefix the data with "big"? In his opinion, the so-called "big" is to emphasize the timeliness of data. In the past, data reports were delayed, and the data provided by the new IOT sensing technology is more real-time and more valuable. Second, it emphasizes relevance. He found that enterprises in the Yangtze River Delta generally use proction management software to promote informatization. However, there are dozens or hundreds of these general-purpose softwares, and the data generated by different softwares are not shared. If there is no correlation effect, no amount of data can be regarded as "small data". Third, we should emphasize "indiviation". The larger the data model is, the more personalized features can be obtained. How to transform the fuzzy personalized demand data of customers into design technical indicators will be the next "tuyere" of instrial big data application
"the real meaning of big data is not big, but diversified." Yuan Yue, a big data instry tycoon and director of Horizon Research and consulting group, said that how to make the multivariate data in the process of aggregation, get scientific analysis results through software processing, and turn them into useful data sources is the significance of establishing big data decision-making system in the field of manufacturing and social management“ Just like in the process of mining, big data is the crude oil in it. Only after refined refining can it be valuable. "
a "brainstorming" lasted three or four hours. In the war of words, a consensus is graally formed - big data ≠ big data; The development of big data instry should be "application-oriented"; Data will be the most important resource for future development, even "driving the future"
crystal ore, Grade 7, distributed in Yanbei and Wuyi. Yanbei needs mining skills: 6, Wuyi needs mining skills: 7
jadeite ore, Grade 8, distributed in Wuyi and Shilin. Wuyi needs mining skills: 7, Shilin needs mining skills: 8
Zhenwu ore, ore grade: 9, distributed in stone forest and grassland. Wuyi needs mining skills: 8, grassland needs mining skills: 9
Longxue ore, ore grade: 10, distributed in grassland and Meiling. Grassland needs mining skills: 9, Meiling needs mining skills: 10.