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USA Computing Olympiad What every computer science major should know Portfolio versus resume Having emerged from engineering and mathematics, computer science programs take a resume-based approach to hiring off their graduates. A resume says nothing of a programmer's ability. Every computer science major should build a portfolio. A portfolio could be as simple as a personal blog, with a post for each project or accomplishment. Contributions to open source should be linked and documented. A code portfolio allows employers to directly judge ability. GPAs and resumes do not. Professors should design course projects to impress on portfolios, and students, at the conclusion of each course, should take time to update them. Examples Technical communication Lone wolves in computer science are an endangered species. Modern computer scientists must practice persuasively and clearly communicating their ideas to non-programmers. Unfortunately, this is not something fixed with the addition of a single class (although a solid course in technical communication doesn't hurt). Java

Ваш персональный курс по Big Data Привет, хабр! После публикации нескольких статей по Big Data и Машинному обучению, ко мне пришло немало писем от читателей с вопросами. За последние несколько месяцев мне удалось помочь многим людям сделать быстрый старт, некоторые из них — уже решают прикладные задачи и делают успехи. А кто-то уже устроился на работу и занимается решением реальных задач. Станьте отличным математиком Да, это наверное самое важное — математическое мышление, которое надо развивать в себе постоянно с младших лет. После того, как вы научитесь оперировать дискретными обьектами, рекомендуется познакомиться с построением эффективных алгоритмов — для этого достаточно пройти небольшой курс по алгоритмам, вроде курса ШАДа или прочитав обзор известных алгоритмов на — довольно популярный сайт среди участников ACM. После того, как ваш мозг научился оперировать с дисретными обьектами, а также развилось алгоритмическое мышление вам необходимо научиться мыслить в терминах теории вероятности.

Omega and why maths has no TOEs December 2005 Over the millennia, many mathematicians have hoped that mathematics would one day produce a Theory of Everything (TOE); a finite set of axioms and rules from which every mathematical truth could be derived. But in 1931 this hope received a serious blow: Kurt Gödel published his famous Incompleteness Theorem, which states that in every mathematical theory, no matter how extensive, there will always be statements which can't be proven to be true or false. Gregory Chaitin has been fascinated by this theorem ever since he was a child, and now, in time for the centenary of Gödel's birth in 2006, he has published his own book, called Meta Math! on the subject (you can read a review in this issue of Plus). It describes his journey, which, from the work of Gödel via that of Leibniz and Turing, led him to the number Omega, which is so complex that no mathematical theory can ever describe it. Kurt Gödel Splattered ink What is complexity? Gottfried von Leibniz Turing's halting problem VisuAlgo was conceptualised in 2011 by Dr Steven Halim as a tool to help his students better understand data structures and algorithms, by allowing them to learn the basics on their own and at their own pace. VisuAlgo contains many advanced algorithms that are discussed in Dr Steven Halim's book ('Competitive Programming', co-authored with his brother Dr Felix Halim) and beyond. Today, some of these advanced algorithms visualization/animation can only be found in VisuAlgo. Though specifically designed for NUS students taking various data structure and algorithm classes (e.g. CS1010, CS1020, CS2010, CS2020, CS3230, and CS3233), as advocators of online learning, we hope that curious minds around the world will find these visualisations useful too. VisuAlgo is not designed to work well on small touch screens (e.g. smartphones) from the outset due to the need to cater for many complex algorithm visualizations that require lots of pixels and click-and-drag gestures for interaction.

Configure conky-Lua in Ubuntu (11.10 & 12.04), Fedora, debian and LinuxMint | Howto Conky Updated 12-10-2013: Conky is a free, light-weight system monitor for X, that displays any information on your desktop. There are many nice themes available for conky that can display clock, CPU usage, ram usage, swap, disk, net and more, one of these nice themes is Conky-Lua, this theme (See screensot bellow) allow you to display nice rings for Clock, cpu …, the theme is available for Ubuntu, Linuxmint, fedora, and Debian. See also Next Generation, another nice conky theme from Conky-Lua author In this post i will show you step by step on how to install and configure this awesome conky script called Conky-Lua. The installation has been done in Ubuntu 12.04 LTS Precise Pangolin also tested in Ubuntu 13.04 and Ubuntu 13.10 Saucy Salamander Raring Ringtail. sudo apt-get install conky-all -For Fedora use : yum install conky-all 2- Download Conky-Loa from this Link 3- Now go to your Download folder and extract manually the file (double click on the archive or right click and select extract) conky

newfinancepage.html Scott Burton Financial Software Projects Graduate Division - Computer Science Tuesday 7:10-9:00 WWH Room WWH 3 This course will be taught by a veteran Wall St. technology manager currently employed at a top tier investment bank. Pre-requisites: It is assumed that the students can code in C++ or C for the server side. No prior experince in the financial sector is required - just a desire to learn it. Reference Materials: Software Engineering: Soul of a New Machine - Tracy Kidder The Mythical Man - Month - Fred Brooks (this is the only text students will need to purchase) Application Domain: (should be available in library): The Handbook of Global Fixed Income Calculations - Dragomir Krgin The Money Markets - Marcia Stigum Security Analysis - Graham and Dodd Handouts Course Objectives: 1. 2. 3. 4. 5. 6. Grading policy: Quizes will be given periodically and will cover topics presented in lectures, handouts and reference texts. 1. 2. 3. 4. 5. 7. 8. Course Evolution: Guest Lectures:

Google Develops AI that is Entirely Self Learning Google scientists and engineers have created the first ever computer program that is capable of learning a wide variety of tasks completely independently, in what is a giant leap towards true general artificial intelligence. The AI, or as Google refers to it the“agent”, has learnt to play almost 50 different retro computer games, and came up with its own strategies for winning completely without human input. The same approach could be used to control self-driving cars or personal assistants in smartphones. This research was conducted at a British company the Google acquired a few years ago called DeepMind Demis Hassabis, who founded DeepMind said: “This is the first significant rung of the ladder towards proving a general learning system can work. And continued to draw comparisons with IBM’s DeepBlue chess computer. “With Deep Blue, it was team of programmers and grand masters that distilled the knowledge into a program. (source Guardian)