Top 10 Algorithms for Coding Interview PDF: Update History, Latest version (8/1/2016) The following are the common subjects in coding interviews. As understanding those concepts requires much more effort, this tutorial only serves as an introduction. The subjects that are covered include: 1) String/Array/Matrix, 2) Linked List, 3) Tree, 4) Heap, 5) Graph, 6) Sorting, 7) Dynamic Programming, 8) Bit Manipulation, 9) Combinations and Permutations, and 10) Math Problems. I highly recommend you to read "Simple Java" first, if you need a brief review of Java basics. 1. An algorithm problem's input is often a string or array. 2. Common methods to solve matrix related problem include DFS, BFS, dynamic programming, etc. 3. The implementation of a linked list is pretty simple in Java. Two popular applications of linked list are stack and queue. Stack Queue The Java standard library contains a class called "Stack". 4. A tree normally refers to a binary tree. Here are some concepts related with trees: 4.1 Tree 4.2 Heap 4.3 Trie 4.4 Segment Tree
Все задачи - Проект Эйлера Пусть sum(A) - сумма элементов для любого множества чисел A. Рассмотрим множество B = {1,3,6,8,10,11}. Существует ровно 20 подмножеств B, которые состоят из трех элементов, а суммы этих подмножеств равны: sum({1,3,6}) = 10, sum({1,3,8}) = 12, sum({1,3,10}) = 14, sum({1,3,11}) = 15, sum({1,6,8}) = 15, sum({1,6,10}) = 17, sum({1,6,11}) = 18, sum({1,8,10}) = 19, sum({1,8,11}) = 20, sum({1,10,11}) = 22, sum({3,6,8}) = 17, sum({3,6,10}) = 19, sum({3,6,11}) = 20, sum({3,8,10}) = 21, sum({3,8,11}) = 22, sum({3,10,11}) = 24, sum({6,8,10}) = 24, sum({6,8,11}) = 25, sum({6,10,11}) = 27, sum({8,10,11}) = 29. Некоторые из этих сумм встречаются более одного раза, другие - уникальны. Теперь, рассмотрим 100-элементное множество S = {1
Download Anaconda now! | Continuum Jump to: Windows | OS X | Linux Get Superpowers with Anaconda Anaconda is the leading open data science platform powered by Python. Which version should I download and install? Because Anaconda includes installers for Python 2.7 and 3.5, either is fine. If you don't have time or disk space for the entire distribution, try Miniconda, which contains only conda and Python. Anaconda for Windows Windows Anaconda Installation Download the graphical installer. Anaconda for OS X OS X Anaconda Installation Choose either the graphical installer or the command line installer for OS X. Graphical Installer: Download the graphical installer. Command Line Installer: Download the command line installer. Anaconda for Linux Linux Anaconda Installation Download the installer. What next? To try out all the features in Anaconda, take the conda 30-minute test drive. Need an older version of Anaconda? For older versions of Anaconda installers, see the Anaconda installer archive.
Essential Computing for Bioinformatics - Dr. Bienvenido Vélez Essential Computing for Bioinformatics This course provides a broad introductory discussion of essential computer science concepts that have wide applicability in the natural sciences. Particular emphasis will be placed on applications to Bioinformatics. NOTE: Most materials are available in source (e.g. General Information Lectures Slides Problem Sets Programming Examples Software Development Tools Useful Links Please let me know of any useful links that you find to post them on ths page. Gödel's Lost Letter and P=NP | a personal view of the theory of computation Практическое руководство по Jekyll Jekyll на Хабрахабре уже светился. Коротко говоря: это система генерации статических сайтов, ориентированная на блоги. Основная особенность: используется на Github Pages, что позволяет держать исходники сайта в репозитории на Github — а несколько кэширующих серверов его в пределах 10 минут после коммитов будут собирать и отображать посетителям. Из всех существующих платформ для блогов (движков, сервисов, генераторов) Jekyll мне показался странно выделяющимся. Написание постов Первое, чем Jekyll отталкивает большинство начинающих: полное отсутствие визуального (WYSIWYG) редактора. Визуальный редактор в Jekyll отстутствует скорее потому, что не очень понятно, куда его девать. Статичность не во вред Второе, чем Jekyll отталкивает: статичность собранного сайта, отсутствие обратной связи. Особенности хостинга на Github Github, в первую очередь, хранилище Git-репозиториев. Если задуматься, Github — одна из самых весомых причин использовать Jekyll. Зачем тут YAML Шаблоны: самое главное! icon: tags
Python « Steve Byrnes's Homepage (Last update: October 2015. Email me if you see errors and omissions.) This page is a guide for how to install Python and start using it for scientific computing. But first: What is Python and why should I use it? Python is a general-purpose programming language. What advantages? To begin: Install Python and Spyder Screenshot of me using Spyder To run and edit scientific programs in Python / NumPy, a great way to start is to use Spyder, a visual interface similar to MATLAB where you can run commands, edit and debug programs, check the values of variables and the definitions of functions, etc. Way back in the day, installing Spyder used to be an annoying multi-step process (first download and install Python itself, then download and install NumPy, SciPy, PyQt, etc., then finally download and install Spyder). Luckily, installation is now very easy: You can download and install all the components together automatically in one step. That’s all you need to know to install Python. Appendix 2: Sage
BME 205 Fall 2013 Bioinformatics: models and algorithms (Last Update: 20:53 PST 26 November 2013 ) link to homeworklink to schedule This is a required course for bioinformatics students—both undergraduate and graduate students (also pre-requisite to BME 230). For catalog copy and pre-requisites, see the main page for BME205. Who, When, and Where: Instructor: Kevin Karplus ( karplus@soe.ucsc.edu) Office hours: PSB 318, W 4–5 +1-831-459-4250 TA: None this year Lectures: MWF 2–3:10 PSB 305 On-line discussion: We have no forum set up for the class this year, but you can subscribe to a Google Groups mailing list bme205@soe.ucsc.edu or view on the web at Texts There will be no required texts, two optional texts, plus additional readings that will be distributed via the Web: Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids from Cambridge University Press by R. BME 205 will be using Python. Homework