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"Open-source software has been on the rise at many businesses during the extended economic downturn, and one of the areas where it is starting to offer companies a lot of flexibility and cost savings is in cloud computing. Cloud deployments can save money, free businesses from vendor lock-ins that could really sting over time, and offer flexible ways to combine public and private applications. The following are 11 top open-source cloud applications, services, educational resources, support options, general items of interest, and more. "

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Pattern recognition is "the act of taking in raw data and taking an action based on the category of the data".[citation needed] Most research in pattern recognition is about methods for supervised learning and unsupervised learning.

Pattern recognition aims to classify data (patterns) based either on a priori knowledge or on statistical information extracted from the patterns. The patterns to be classified are usually groups of measurements or observations, defining points in an appropriate multidimensional space. This is in contrast to pattern matching, where the pattern is rigidly specified.

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Pattern recognition wikipedia info reference computing computer science tech patterns

In computer science, pattern matching is the act of checking for the presence of the constituents of a given pattern. In contrast to pattern recognition, the pattern is rigidly specified. Such a pattern concerns conventionally either sequences or tree structures. Pattern matching is used to test whether things have a desired structure, to find relevant structure, to retrieve the aligning parts, and to substitute the matching part with something else.

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This course is designed to serve as a first course in an undergraduate electrical engineering (EE), or electrical engineering and computer science (EECS) curriculum.

The course introduces the fundamentals of the lumped circuit abstraction. Topics covered include: resistive elements and networks; independent and dependent sources; switches and MOS transistors; digital abstraction; amplifiers; energy storage elements; dynamics of first- and second-order networks; design in the time and frequency domains; and analog and digital circuits and applications. Design and lab exercises are also significant components of the course. The course content was created collaboratively by Profs. Anant Agarwal and Jeffrey H. Lang.

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Computer Science 15 courses and 2 guest lectures

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EE 380: Computer Systems Laboratory Colloquium is a Stanford University course that features weekly speakers on current research and developments in computer systems. Topics touch upon all aspects of computer science and engineering including logic design, computer organization and architecture, software engineering, computer applications, public policy, and the social, business, and financial implications of technology. Frequently the Colloquium provides the first public forum for discussion of new products, discoveries, or ideas. This playlist consists of seminar speakers recorded during the 2007-2008 academic year.
1 year ago 5,673 views stanforduniversity

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EE 380: Computer Systems Laboratory Colloquium is a Stanford University course that features weekly speakers on current research and developments in computer systems. Topics touch upon all aspects of computer science and engineering including logic design, computer organization and architecture, software engineering, computer applications, public policy, and the social, business, and financial implications of technology. Frequently the Colloquium provides the first public forum for discussion of new products, discoveries, or ideas. This playlist consists of seminar speakers recorded during the 2006-2007 academic year.
1 year ago 4,543 views stanforduniversity

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Programming Paradigms (CS107) introduces several programming languages, including C, Assembly, C++, Concurrent Programming, Scheme, and Python. The class aims to teach students how to write code for each of these individual languages and to understand the programming paradigms behind these languages.
10 months ago 38,044 views stanforduniversity

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CS 61B: Data Structures - Fall 2006. Fundamental dynamic data structures, including linear lists, queues, trees, and other linked structures; arrays strings, and hash tables. Storage management. Elementary principles of software engineering. Abstract data types. Algorithms for sorting and searching. Introduction to the Java programming language.
10 months ago 38,268 views ucberkeleyy

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Search Engines: Technology, Society, and Business. The World Wide Web brings much of the world's knowledge into the reach of nearly everyone with a computer and an internet connection. The availability of huge quantities of information at our fingertips is transforming government, business, and many other aspects of society.
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This course exposes students to techniques of abstraction at several levels: (a) within a programming language, using higher-order functions, manifest types, data-directed programming, and message-passing; (b) between programming languages, using functional and rule-based languages as examples. Lectures 5 & 6 contain copyright material and will be public when permission is granted.
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This course (CS 106B) is the successor to CS 106A and covers more advanced programming topics such as recursion, algorithmic analysis, and data abstraction. It is taught using the C++ programming language, which is similar to both C and Java. In the past when both CS 106A and CS106B were taught in C/C++, the coupling between the two classes was very tight and it was unheard for students to take CS106B without having completed our CS 106A (we recommended CS 106X instead). Nowadays, some students do go straight into CS106B, this is typically appropriate for a student who done well in an intro programming course (e.g., scored 4 or 5 on the CS AP exam or earned a good grade in a college course) and has sufficient familiarity with good programming style and software engineering issues (at the level of CS 106A) to use this understanding as a foundation on which to tackle advanced topics.
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Programming Methodology (CS106A) is an Introduction to the engineering of computer applications emphasizing modern software engineering principles: object-oriented design, decomposition, encapsulation, abstraction, and testing. Uses the Java programming language. Emphasis is on good programming style and the built-in facilities of the Java language.
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Obsessable covers the latest in the world of technology, including cell phones, digital cameras, and HDTVs - obsessively, of course. Obsessable is powered by the rapid content development engine, Crowd Fusion.

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MapReduce is a software framework originally developed by Google to support parallel computations over large (greater than 100 terabyte) data sets on unreliable clusters of computers. The name is derived from the map and reduce functions commonly used in

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At the Tech FAQ, the technical answers you have been looking for are answered in detail, yet in a way the average person can understand. The problem with many technical websites that seek to explain technical questions is they are frequently over the comp

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The Java Tutorials are practical guides for programmers who want to use the Java programming language to create applications. They include hundreds of complete, working examples, and dozens of lessons. Groups of related lessons are organized into "trails".

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by Eric Raymond \n\n\nMy first look at Python was an accident, and I didn't much like what I saw at the time. It was early 1997, and Mark Lutz's book Programming Python from O'Reilly & Associates had recently come out. O'Reilly books occasionally land on my doorstep, selected from among the new releases by some mysterious benefactor inside the organization using a random process I've given up trying to understand.

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