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Translating large data into large value practical strategies

Today, some of the most successful companies gain a strong business advantage by capturing, analyzing, and leveraging a large variety of "big data" that is fast moving. This article describes three usage models that can help you implement a flexible, efficient, large data infrastructure to gain a competitive advantage in your business. This article also describes Intel's many innovations in chips, systems, and software to help you deploy these and other large data solutions with optimal performance, cost, and energy efficiency. Big Data opportunities People often compare big data to tsunamis. Currently, the global 5 billion mobile phone users and nearly 1 billion of Facebo ...

Prismatic: It takes only 10 seconds to learn to analyze users ' interests by machine

There are a few things to explain about prismatic first. Their entrepreneurial team is small, consisting of just 4 computer scientists, three of them young Stanford and Dr. Berkeley. They are using wisdom to solve the problem of information overload, but these PhDs also act as programmers: developing Web sites, iOS programs, large data, and background programs for machine learning needs. The bright spot of the prismatic system architecture is to solve the problem of social media streaming in real time with machine learning. Because of the trade secret reason, he did not disclose their machine ...

Data scientists don't need too much to make big data easy enough

Editor's note: The New York Times has written Pro Data age has come, http://www.aliyun.com/zixun/aggregation/13768.html "> Data scientists have been dubbed the most sexy occupation, but E-commerce consulting company Jack's founder and CTO Scott Brave says we don't need more data scientists to make big data easier to use. Here's what he thinks: Big numbers are hot this year, so the New York Times ...

Infosphere streams a large data platform for analyzing mobile

Information from multiple sources is growing at an incredible rate. The number of Internet users has reached 2.27 billion in 2012. Every day, Twitter generates more than TB of tweet,facebook to generate more than TB log data, and the New York Stock Exchange collects 1 TB of trading information. Approximately 30 billion radio frequency identification (RFID) tags are created every day. In addition, the annual sales of hundreds of millions of GPS equipment, is currently using more than 30 million network sensing ...

Sweep 13 Open source Java Large data tools, from theory to practice analysis

Big data has almost become the latest trend in all business areas, but what is the big data? It's a gimmick, a bubble, or it's as important as rumors. In fact, large data is a very simple term--as it says, a very large dataset. So what are the most? The real answer is "as big as you think"! So why do you have such a large dataset? Because today's data is ubiquitous and has huge rewards: RFID sensors that collect communications data, sensors to collect weather information, and g ...

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Old code farmer: How to write code that satisfies you

Intermediary transaction http://www.aliyun.com/zixun/aggregation/6858.html ">seo diagnose Taobao guest cloud host technology Hall today, a friend on Weibo asked me such a question:" @ Old code agricultural plots, recently out of learning To write a management system, the more to the back, the more I feel that the code in front of me is rotten.   Senior, I want to let the code write better, can you talk about your experience, give me some pointers! " I am replying ...

Why do some companies prefer to use the R + Hadoop solution in the machine learning business?

Introduction: It is well known that R is unparalleled in solving statistical problems. But R is slow at data speeds up to 2G, creating a solution that runs distributed algorithms in conjunction with Hadoop, but is there a team that uses solutions like python + Hadoop? R Such origins in the statistical computer package and Hadoop combination will not be a problem? The answer from the king of Frank: Because they do not understand the characteristics of R and Hadoop application scenarios, just ...

Recommended! The machine learning resources compiled by foreign programmers

C + + computer vision ccv-based on C language/provides cache/core machine Vision Library, novel Machine Vision Library opencv-It provides C + +, C, Python, Java and MATLAB interfaces, and supports Windows, Linux, Android and Mac OS operating system. General machine learning Mlpack dlib Ecogg Shark Closure Universal machine learning Closure Toolbox-cloj ...

What is machine learning? Why is it so important?

Machine learning is a multi-disciplinary subject that has emerged in the past 20 years and involves many disciplines such as probability theory, statistics, approximation theory, convex analysis, and computational complexity theory.

Cloud storage: Opportunities for hidden challenges

Total IT spending on cloud computing will grow at least 3 times times by 2012, according to projections. For cloud computing, from the perspective of the IT department, Enterprise Cloud computing is expected to provide resilient scalability, pay-as-you-go and predictable cost structures, while improving data access mechanisms.   From a business unit perspective, this means being able to turn asset costs into operational costs, improve productivity and innovation, while reducing it costs and operating costs. The technical maturity makes the practical cloud solution both available and affordable. At present, most big enterprises are already groping some method, ...

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