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Algorithms are implemented in Java. This is for education purpose only. Algorithms include Sorting, Search Algorithms, Dynamic Programming, Ciphers, Data Structures and few more.

https://github.com/TheAlgorithms/JavaTags | algorithms implementation algorithms-implemented algorithms-datastructures algorithm-challenges wiki reference tutorial |

Implementation | Java |

License | Public |

Platform | OS-Independent |

There are several data structures and algorithms implemented in this project. The list will be replenished with time. The library is not intended for direct use by importing. We strongly recommend copying the necessary implementations and adjusting to your case.

datastructures algorithms algorithms-datastructures algorithms-and-data-structures algorithm data-structuresA C# plug-and-play class-library project of standard Data Structures and Algorithms. It contains 35+ Data Structures and 30+ Algorithms designed as Object-Oriented isolated components. Even though this project started for educational purposes, the implemented Data Structures and Algorithms are standard, efficient, stable and tested.This project originally started out as an interview preparation project. However, after receiving a great amount of positive responses on reddit, and noticing excitement from a few GitHubers to contribute furthermore to it, the project took on a different meaning. So, I decided to keep maintaining it as a reference for data structures and algorithm implementations in C# as well as my own research side-project under these topics.

algorithms data-structures graph graph-algorithms tree binary-trees algorithmTarsosDSP is a Java library for audio processing. Its aim is to provide an easy-to-use interface to practical music processing algorithms implemented, as simply as possible, in pure Java and without any other external dependencies. The library tries to hit the sweet spot between being capable enough to get real tasks done but compact and simple enough to serve as a demonstration on how DSP algorithms works. TarsosDSP features an implementation of a percussion onset detector and a number of pitch detection algorithms: YIN, the Mcleod Pitch method and a “Dynamic Wavelet Algorithm Pitch Tracking” algorithm. Also included is a Goertzel DTMF decoding algorithm, a time stretch algorithm (WSOLA), resampling, filters, simple synthesis, some audio effects, and a pitch shifting algorithm. To show the capabilities of the library, TarsosDSP example applications are available. Head over to the TarosDSP release directory for freshly baked binaries and code smell free (that is the goal anyway), oven-fresh sources.

Community (college) maintained list of Algorithms and Data Structures implementations. See CONTRIBUTING.md.

algorithm algorithms algorithm-challenges data-structures codes code-listSource code of Learning JavaScript Data Structures and Algorithms book.

javascript-algorithms algorithm data-structures typescript typescript-algorithms stack queue deque priority-queue linked-list set tree sorting-algorithms dictionary binary-tree avl-tree quicksort graph graph-algorithms dijkstra-algorithmThis is a collection of algorithms and data structures which I've implement over the years in my academic and professional life. The code isn't overly-optimized but is written to be correct and readable. The algorithms and data structures are well tested and, unless noted, are believe to be 100% correct.

algorithm sort graph tree data-structuresCosmos is your personal offline collection of every algorithm and data structure one will ever encounter and use in a lifetime. This provides solutions in various languages spanning C, C++, Java, JavaScript, Swift, Python, Go and others. This work is maintained by a community of hundreds of people and is a massive collaborative effort to bring the readily available coding knowledge offline.

opengenus algorithm datastructures library offline-app interview-questions sorting-algorithms search-algorithmsOverhauled to now include 120 challenges and solutions and added Anki flashcards.Also included are unit tested reference implementations of various data structures and algorithms.

algorithm data-structure development programming coding interview interview-questions interview-practice competitive-programming:crown: LeetCode of algorithms with java solution(updating).

leetcode leetcode-solutions leetcode-java facebook datastructure datastructures algorithm algorithmsMy solutions to some of the algorithm and data structure questions in Java

algorithm interview datastructures data-structures hackerrank hackerrank-solutions geeksforgeeks coding-interviews interview-practice interview-preparation java-8 cracking-the-coding-interview cracking-the-technical-interview cracking-code-interview coding-interviewThis repository contains JavaScript based examples of many popular algorithms and data structures. Each algorithm and data structure has its own separate README with related explanations and links for further reading (including ones to YouTube videos).

algorithms algorithm javascript-algorithms computer-science interview data-structures interview-preparation cs sorting-algorithms graph treeClever Algorithms: Nature-Inspired Programming Recipes is an open source book that describes a large number of algorithmic techniques from the the fields of Biologically Inspired Computation, Computational Intelligence and Metaheuristics in a complete, consistent, and centralized manner such that they are accessible, usable, and understandable. This is a repository for the book project used during the development and ongoing maintenance of the books’ content. Implementing an Artificial Intelligence algorithm is difficult. Algorithm descriptions may be incomplete, inconsistent, and distributed across a number of papers, chapters and even websites. This can result in varied interpretations of algorithms, undue attrition of algorithms, and ultimately bad science. This book is an effort to address these issues by providing a handbook of algorithmic recipes drawn from the fields of Metaheuristics, Biologically Inspired Computation and Computational Intelligence, described in a complete, consistent, and centralized manner. These standardized descriptions were carefully designed to be accessible, usable, and understandable. Most of the algorithms described were originally inspired by biological and natural systems, such as the adaptive capabilities of genetic evolution and the acquired immune system, and the foraging behaviors of birds, bees, ants and bacteria. An encyclopedic algorithm reference, this book is intended for research scientists, engineers, students, and interested amateurs. Each algorithm description provides a working code example in the Ruby Programming Language.

If you spot any errors in the implementation(s), please let me know by submitting a relevant pull request. Furthermore, if you'd like to see a particular data structure or algorithm implemented here, let me know by raising an issue.

algorithms data-structures c-plus-plusThese are for demonstration purposes only. There are many implementations of sorts in the Python standard library that are much better for performance reasons. From Wikipedia: Bubble sort, sometimes referred to as sinking sort, is a simple sorting algorithm that repeatedly steps through the list to be sorted, compares each pair of adjacent items and swaps them if they are in the wrong order. The pass through the list is repeated until no swaps are needed, which indicates that the list is sorted.

algorithm algorithms-implemented algorithm-competitions algos sorts searches sorting-algorithms education learn practice community-driven interviewThis repository contains JavaScript implementations of different famous Computer Science algorithms.API reference with usage examples available here.

computer-science-algorithms algorithmThis repository contains some useful algorithms and data structures. How you can contribute? See this small guide.

cpp algorithm algorithms-implemented data-structures algorithm-competitionsThis repository contains implementations of basic machine learning algorithms in plain Python (Python Version 3.6+). All algorithms are implemented from scratch without using additional machine learning libraries. The intention of these notebooks is to provide a basic understanding of the algorithms and their underlying structure, not to provide the most efficient implementations. After several requests I started preparing notebooks on how to preprocess datasets for machine learning. Within the next months I will add one notebook for each kind of dataset (text, images, ...). As before, the intention of these notebooks is to provide a basic understanding of the preprocessing steps, not to provide the most efficient implementations.

machine-learning logistic-regression ipynb machine-learning-algorithms linear-regression perceptron python-implementations kmeans algorithm python3 neural-network k-nearest-neighbours k-nearest-neighbor k-nn neural-networksThe library contains a number of interconnected Java packages that implement machine learning and artificial intelligence algorithms. These are artificial intelligence algorithms implemented for the kind of people that like to implement algorithms themselves. See Issues page.

artificial-intelligence-algorithms neural-network machine-learning optimization-algorithmsRead the research paper BF-Programmer: A Counterintuitive Approach to Autonomously Building Simplistic Programs Using Genetic Algorithms. AI-Programmer is an experiment with using artificial intelligence and genetic algorithms to automatically generate programs. Successfully created programs by the AI include: hello world, hello , addition, subtraction, reversing a string, fibonnaci sequence, 99 bottles of beer on the wall, and more. It's getting smarter. In short, it's an AI genetic algorithm implementation with self modifying code.

genetic-algorithms c-sharp fitness-score ai artificial-intelligence genetic-algorithm genetic-programming programming-language genome program-synthesisIn this course you will learn how to Analysis algorithms like Sorting, Searching, and Graph algorithms. And how to reduce the code complexity from one Big-O level to another level. Furthermore, you will learn different type of Data Structure for your code. Also you will learn how to find Big-O for every data structure, and how to apply correct Data Structure to your problem in Java. By the end you will be able to write code that run faster and use low memory. You Also will learn how to analysis problems using Dynamic programming.

algorithm algorithm-analysis analysis-algorithms complexity job-interviews graph-algorithms sort
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