abxda : #BigData Tiene que ver con... mindyourdecisions.com abxda : #BigData la perspectiva de... Motor cognition The concept of motor cognition grasps the notion that cognition is embodied in action, and that the motor system participates in what is usually considered as mental processing, including those involved in social interaction.[1] The fundamental unit of the motor cognition paradigm is action, defined as the movements produced to satisfy an intention towards a specific motor goal, or in reaction to a meaningful event in the physical and social environments. Motor cognition takes into account the preparation and production of actions, as well as the processes involved in recognizing, predicting, mimicking and understanding the behavior of other people. This paradigm has received a great deal of attention and empirical support in recents years from a variety of research domains including developmental psychology, cognitive neuroscience, and social psychology. Perception-action coupling[edit] Shared representations between other and self[edit] Motor priming[edit] Social facilitation[edit]
Zeichick’s Take: Ignore Hadoop at your peril It’s the best software platform named for a toy elephant, and it’s hard to imagine designing a modern data-intensive application without seriously considering Apache’s Hadoop ecosystem as a way to distribute the workload. Hadoop has the same ability to revolutionize data handling that the Apache HTTP server did for websites nearly two decades ago, or what Tomcat did for Web applications, or what Subversion and Git are doing for collaborative software development. Don’t take my word for it. The demand for Hadoop is increasing globally due to its capability to access data faster and at cheaper cost as compared to RDBMS. Certainly you hear all about Hadoop, and its many affiliated projects, in every Big Data-related conversation, and of course in sessions at events like Big Data TechCon, coming to San Francisco on Oct. 15-17. Yes, Map/Reduce, the paradigm behind Hadoop, is not ideal for every task. Hadoop.
Networks, Crowds, and Markets: A Book by David Easley and Jon Kleinberg In recent years there has been a growing public fascination with the complex "connectedness" of modern society. This connectedness is found in many incarnations: in the rapid growth of the Internet and the Web, in the ease with which global communication now takes place, and in the ability of news and information as well as epidemics and financial crises to spread around the world with surprising speed and intensity. These are phenomena that involve networks, incentives, and the aggregate behavior of groups of people; they are based on the links that connect us and the ways in which each of our decisions can have subtle consequences for the outcomes of everyone else. Networks, Crowds, and Markets combines different scientific perspectives in its approach to understanding networks and behavior. The book is based on an inter-disciplinary course that we teach at Cornell. The book, like the course, is designed at the introductory undergraduate level with no formal prerequisites.
Busting 10 myths about Hadoop Although Hadoop and related technologies have been with us for more than five years now, most BI professionals and their business counterparts still harbor a few misconceptions that need to be corrected about Hadoop and related technologies such as MapReduce. The following list of 10 facts will clarify what Hadoop is and does relative to BI/DW, as well as in which business and technology situations Hadoop-based business intelligence (BI), data warehousing (DW), data integration (DI), and analytics can be useful. Fact No. 1: Hadoop consists of multiple products We talk about Hadoop as if it's one monolithic thing, but it's actually a family of open-source products and technologies overseen by the Apache Software Foundation (ASF). (Some Hadoop products are also available via vendor distributions; more on that later.) The Apache Hadoop library includes (in BI priority order): the Hadoop Distributed File System (HDFS), MapReduce, Pig, Hive, HBase, HCatalog, Ambari, Mahout, Flume, and so on.
Introduction to Computer Science Class Online (CS101) When does the course begin? This class is self paced. You can begin whenever you like and then follow your own pace. It’s a good idea to set goals for yourself to make sure you stick with the course. How long will the course be available? This class will always be available! How do I know if this course is for me? Take a look at the “Class Summary,” “What Should I Know,” and “What Will I Learn” sections above. Can I skip individual videos? Yes! What are the rules on collaboration? Collaboration is a great way to learn. Why are there so many questions? Udacity classes are a little different from traditional courses. What should I do while I’m watching the videos? Learn actively!