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Application of data Mining in medicine

This article will talk about the application of data mining in medicine, hope to be interested in the friends have inspiration, but also engaged in other industries data mining applications colleagues reference. Data mining, also known as Knowledge Discovery (KDD), is the process of extracting potential and valuable knowledge from a large number of data. The pattern explored by data mining is an objective, but hidden knowledge that is not found in data. For example, data mining can directly excavate the high disease population, discover the unknown link between the disease and the symptom, explore the influence relationship between the test indexes and the potential influence between the test index and the disease, to the unknown ...

Reflection on the development of cloud computing and profit model of telecom operators

I. Introduction at present, the world is in the beginning of the third wave of information technology revolution, cloud computing will become the latest "subversive" driving force, improve social productivity, promote the overall information level of society, and completely subvert the current business model and system.   According to Gartner, Global cloud computing services are about $100 billion trillion in 2012, with annual growth expected to exceed 20% per cent in the next few years, and 176.8 billion trillion dollars in the global cloud computing services market in 2015. Generalized Cloud Meter ...

14 Questions for Silicon Valley and Silicon Valley technology companies: Valuation Bubbles/Big Data

From the Silicon Valley firm, to everyone's discussion of the bubble problem, how large data and artificial intelligence combined? What is the prospect of science and technology in the 2015? Dong Fei, a Coursera software engineer from Silicon Valley, sorted out the dry goods and various occasions in his recent Stanford public lectures to share with you. He has a hands-on experience, as well as a detailed analysis of some of the companies that have worked or studied in depth, such as Hadoop, Amazon, and LinkedIn. Dong Fei page Here, the mailbox is Dongfeiwww@gmail ....

"What to think" and "What to eat" is an artificial intelligence contest

"What to think" and "what to eat" the two factions have been in the field of artificial intelligence two classes, two lines of struggle, this struggle is sometimes a life-and-death. Set a vulgar philosophical word, the former partial idealism, the latter biased materialism. Computer field now the most popular word is "depth learning" linguist Steve Pink the theory of neural networks to challenge Turing test to open the field of artificial intelligence in the battle of two routes in the field of artificial intelligence large Neumaichel _ Abib, founded the University of Massachusetts computer department. Since Turing proposed ...

Is the age of legal data coming?

The big data age is making the law ever more powerful, in today's digital age, big data is extremely important, especially for law firms, where legal business may eventually be driven by data, when we can judge whether he or she is a good lawyer through the ability of a lawyer to sift through thousands of potentially relevant cases. With the acquisition of massive amounts of data, analysis is becoming more important. New tools to validate legal information, organize, and even visualize legal information are helping legal workers to gain access to massive court information, as storage becomes cheaper and processors become faster ...

The whole network unmanned bicycle "Big Bang"

Text / Internet Han Chinese paper Yesterday morning, an article on Baidu is r & d unmanned bicycle rumors instantly spread to the Internet, prompting the major media competing coverage for the first time. Despite the rumors concentrated in the early morning and morning rush hours, but did not "block" the attention of the majority of white-collar workers, a few hours, paste it, know, microblogging, forums, qq group, bbs, friends circle, everywhere Are all about Baidu research and development of unmanned bicycle news, users discussed enthusiasm quickly detonated by the explosive news. Midday, reported that Netease technology to Baidu seeking ...

Deep learning yesterday, today and tomorrow

Since 2006, a topic called deep learning in the field of machine learning has begun to receive widespread attention in the academic world. Today it has become a boom in Internet big data and artificial intelligence.

Online education website coursera:280 million students ' free University

Is it a pioneer experiment or a profound educational change? The educational tsunami that Coursera led has surged. Guiyun this spring Festival, in Shanghai Hongqiao Airport, Microsoft Research Asia Vice Dean Zhang Yi side while waiting for luggage while using mobile phone to watch "The United States Contemporary Poetry" course, this lecture on William Carlos Williams, he is one of the 20th century most famous poets in the United States. The video is full of bearded Professor Al Filreis of the University of Pennsylvania and several students sitting around a wooden round table, FILR ...

14 Questions for Silicon Valley and Silicon Valley technology companies

Absrtact: 1, what is the hottest and most famous High-tech start-up company in Silicon Valley? In Silicon Valley, we are very enthusiastic about the opportunity to talk about entrepreneurship, I also through their own some observation and accumulation, saw a lot of recent years, the emergence of the popular start-up companies. I'll give you a 1. What are the hottest and most famous High-tech startups in Silicon Valley at the moment? In Silicon Valley, we are very enthusiastic about the opportunity to talk about entrepreneurship, I also through their own some observation and accumulation, saw a lot of recent years, the emergence of the popular start-up companies. I give you a list, this is the Wall Street website of the whole world ...

How to choose an open source machine learning framework

Open source machine learning tools also allow you to migrate learning, which means you can solve machine learning problems by applying other aspects of knowledge.

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