Found 33 results for "tag:algorithms"

• Algorithms by Jeff Erickson

  https://jeffe.cs.illinois.edu/teaching/algorithms/

  algorithms

• Algorytmy i struktury danych

  https://navoica.pl/courses/course-v1:ZPSB+ASD2+2021_ASD2/about

  Kurs pozwala inaczej spojrzeć na zagadnienia, z którymi możesz się zmierzyć podczas rozwiązywania bardziej złożonych problemów programistycznych.

  algorithms

• An Applied Programming Instructor Commentates an Algorithms Class, Pt. 1

  https://chelseatroy.com/2021/10/18/an-applied-programming-instructor-commentates-an-algos-class-1/

  There are two courses that seem to universally strike fear in my students’ hearts. One of them is algorithms. I hear about this dingdang class from multiple students every quarter. Most of my…

  algorithms

• An Applied Programming Instructor Commentates an Algorithms Class, Pt. 2

  https://chelseatroy.com/2021/11/20/an-applied-programming-instructor-commentates-an-algorithms-class-pt-2/

  The title basically captures it: I’m walking through a videotaped algorithms class and recording my observations as a teacher of applied programming classes. Here’s the whole series so …

  algorithms

• Big O

  https://samwho.dev/big-o/?utm_source=hackernewsletter&utm_medium=email&utm_term=fav

  A visual introduction to big O notation.

  algorithms

• CSES - CSES Problem Set - Tasks

  https://cses.fi/problemset/

  algorithms

• Data Structure Visualization

  https://www.cs.usfca.edu/~galles/visualization/Algorithms.html

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• Data Structures and Algorithms Full Course

  https://www.youtube.com/watch?v=0W9sY9Uf8JM

  Welcome to our course! Dive into computational complexity, Big O, and P vs. NP. Learn numerical algorithms, data structures like linked lists and arrays, and master sorting and searching. Explore hash tables, recursion, trees, and graphs. Finish prepared for advanced studies or a tech career. Embrace programming's power! *Chapters and Timestamps:* 00:00:00 - **Chapter 1 - Course Introduction** 00:00:00 - Introduction And Course Overview 00:03:16 - **Chapter 2 - Understanding Complexity** 00:03:16 - Complexity Theory 00:07:12 - Big O Notation 00:14:15 - Typical Runtime Functions 00:18:52 - Comparing Runtime Functions 00:24:19 - P And NP 00:28:23 - **Chapter 3 - Exploring Numerical Algorithms** 00:28:23 - Random Numbers 00:30:42 - Linear Congruential Generators 00:35:46 - Randomizing Arrays - Part 1 00:39:33 - Randomizing Arrays - Part 2 00:44:04 - GCD (Greatest Common Divisor) 00:48:13 - LCM (Least Common Multiple) 00:51:42 - Prime Factorization - Part 1 00:56:41 - Prime Factorization - Part 2 00:59:24 - Finding Primes 01:02:48 - Testing Primality 01:06:34 - Numerical Integration 01:11:45 - **Chapter 4 - Mastering Linked Lists** 01:11:45 - Singly Linked Lists - Part 1 01:18:33 - Singly Linked Lists - Part 2 01:20:56 - Sorted Linked Lists 01:24:19 - Data Break 01:24:34 - Sorting With Linked Lists 01:28:42 - Doubly Linked Lists 01:32:34 - **Chapter 5 - Working with Arrays** 01:32:34 - One-Dimensional Arrays 01:37:44 - Triangular Arrays - Part 1 01:41:57 - Triangular Arrays - Part 2 01:45:15 - Sparse Arrays - Part 1 01:50:43 - Sparse Arrays - Part 2 01:54:03 - **Chapter 6 - Stacks And Queues In-Depth** 01:54:03 - Stacks 01:56:36 - Stack Algorithms 02:00:03 - Double Stacks 02:02:12 - Queues 02:08:01 - **Chapter 7 - Advanced Sorting Techniques** 02:08:01 - Sorting Algorithms 02:11:05 - Insertionsort 02:17:33 - Selectionsort 02:22:20 - Quicksort - Part 1 02:28:00 - Quicksort - Part 2 02:35:55 - Heapsort - Part 1 02:42:12 - Heapsort - Part 2 02:47:33 - Heapsort - Part 3 02:53:13 - Mergesort - Part 1 02:57:09 - Mergesort - Part 2 03:00:50 - Bubblesort - Part 1 03:05:41 - Bubblesort - Part 2 03:10:09 - Countingsort - Part 1 03:14:55 - Countingsort - Part 2 03:18:30 - Sorting Summary 03:21:21 - **Chapter 8 - Searching Techniques** 03:21:21 - Linear Search 03:23:33 - Binary Search 03:28:48 - Interpolation Search 03:34:15 - **Chapter 9 - Fundamentals of Hash Tables** 03:34:15 - Hash Tables 03:38:48 - Chaining 03:44:12 - Open Addressing - Basics 03:51:38 - Open Addressing - Linear Probing 03:56:26 - Open Addressing - Quadratic Probing 04:00:49 - Open Addressing - Double Hashing 04:06:45 - Data Structures Break 04:07:00 - **Chapter 10 - Recursive Algorithms Explained** 04:07:00 - Recursion Basics 04:12:37 - Fibonacci Numbers 04:18:45 - Tower Of Hanoi 04:24:53 - Koch Curves 04:29:25 - Hilbert Curves 04:34:57 - Gaskets 04:39:49 - Removing Tail Recursion 04:43:45 - Removing Recursion With Stacks 04:47:41 - Fixing Fibonacci 04:55:06 - Selections 04:59:22 - Permutations 05:03:34 - **Chapter 11 - Backtracking Techniques** 05:03:34 - Backtracking 05:09:38 - The Eight Queens Problem - Part 1 05:15:39 - The Eight Queens Problem - Part 2 05:19:43 - The Eight Queens Problem - Part 3 05:23:32 - The Knights Tour 05:27:53 - **Chapter 12 - Exploring Tree Structures** 05:27:53 - Tree Terms 05:32:59 - Binary Tree Properties 05:39:24 - Traversals - Preorder 05:43:19 - Traversals - Postorder 05:46:16 - Traversals - Inorder 05:49:04 - Traversals - Breadth-First 05:52:02 - Building Sorted Trees 05:55:58 - Editing Sorted Trees 06:00:34 - **Chapter 13 - Balancing Tree Structures** 06:00:34 - Why Do You Need Balanced Trees? 06:04:38 - Data Structures Break 06:04:46 - B-Trees - B-Tree Basics 06:12:05 - B-Trees - Adding Items 06:17:21 - B-Trees - Removing Items 06:21:37 - **Chapter 14 - Navigating Decision Trees** 06:21:37 - Definition 06:27:14 - Exhaustive Search 06:33:41 - Branch And Bound 06:42:07 - Heuristics 06:49:45 - **Chapter 15 - Network Algorithm Basics** 06:49:45 - Network Terminology 06:53:17 - Network Classes 06:58:10 - Depth-First Traversal 07:03:31 - Breadth-First Traversal 07:06:15 - Spanning Trees - Part 1 07:10:28 - Spanning Trees - Part 2 07:14:26 - Shortest Paths - Part 1 07:21:53 - Shortest Paths - Part 2 07:30:35 - **Chapter 16 - Course Conclusion** 07:30:35 - Wrap-Up Show your Love & Support: https://www.patreon.com/alphabrains ☕️ [Buy me a coffee!] (https://www.buymeacoffee.com/alphabrains) Would Help me make more content like this one :) ``` If you are involved in ANY form of online collaboration, then have I got the all-in-one solution for you! Try it here *(it's completely free)* - https://www.taskade.com/?via=taskade 🌟*Join Our Brainers Community! *🌟 🚀 🧠*Telegram*: https://t.me/+pIXV6rmfKbU5YmRk ✨ *WhatsApp Channel:* https://whatsapp.Com/channel/0029V51YH9p05MUXZRubWa35 🔥*Discord Channel:* https://discord.gg/fbsKcU7mp5 💎*YouTube Channel:* https://www.youtube.com/@alphabrainscourses

  algorithms

• Day 1 | Advent of Code 2024

  https://www.youtube.com/@Errichto/videos

  Solution for problem 1 of Advent of Code 2024, "Historian Hysteria". https://adventofcode.com/ 0:00 Statement 1:29 Solution 3:00 Hard Version I make educational videos on algorithms, coding interviews and competitive programming.

  algorithms

• Every Data Structure on 1 Page - DeriveIt

  https://deriveit.org/coding/every-data-structure-on-1-page-87

  Array An Array is an ordered list of elements. Each element lives at an index 0, 1, 2, and so on. Arrays are also called "lists" in Python. ``` arr = [1, 3, 3, 7] for val in arr: 1,3,3,7 7 in arr True, takes O(n) arr[3] read O(1) arr[3] = 8 write O(1) arr.insert(1, 9) insert O(n) del arr[1] delete O(n) arr.append(9) insert last element O(1) arr.pop() delete last element O(1) ``` Read/Write Time O(1) . Insert/Delete Time O(n) . Stack A Stack is an Array, but where you only Insert/Delete the last

  algorithms

• Free-Algorithm-Books/README.md at master · cjbt/Free-Algorithm-Books · GitHub

  https://github.com/cjbt/Free-Algorithm-Books/blob/master/README.md

  algorithms

• GitHub - cloudanum/50Algorithms

  https://github.com/cloudanum/50Algorithms

  Contribute to cloudanum/50Algorithms development by creating an account on GitHub.

  algorithms

• Introduction to Algorithms | Electrical Engineering and Computer Science | MIT OpenCourseWare

  https://ocw.mit.edu/courses/6-006-introduction-to-algorithms-spring-2020/

  This course is an introduction to mathematical modeling of computational problems, as well as common algorithms, algorithmic paradigms, and data structures used to solve these problems. It emphasizes the relationship between algorithms and programming and introduces basic performance measures and analysis techniques for these problems.

  algorithms

• Introduction to algorithms 3rd%20 edition

  https://edutechlearners.com/download/Introduction_to_algorithms-3rd%20Edition.pdf

  algorithms

• Introduction — Data Structures and Information Retrieval in Python

  https://allendowney.github.io/DSIRP/

  algorithms

• Lazy recursion, with generators

  https://tushar.lol/post/recursive-generators/

  Name a better pairing, I'll wait.

  algorithms

• MAP - Mistrzostwa w Algorytmice i Programowaniu

  https://www.youtube.com/@map-mistrzostwawalgorytmic7237/videos

  Projekt "Mistrzostwa w Algorytmice i Programowaniu i Uczniowie" jest finansowany ze środków pochodzących z "Programu Rozwoju Talentów Informatycznych na lata 2019-2029" Dofinansowanie Projektu: 4.887.850,50 zł Całkowita wartość Projektu: 5.460.850,50 zł

  algorithms

• Mobilo - YouTube

  https://www.youtube.com/@Mobilo24eu/playlists

  Filmy i tutoriale szkoleniowe Kurs PowerShell dla administratora Windows. Kurs SQL - instalacja i narzędzia Kurs SQL - budowa zapytań SQL Kurs SQL - typy zaawansowane, programowanie, XML Kurs Python dla początkujących Promocja ograniczona ilością aktywacji - z kuponem YOUTUBE każdy kurs po 35 zł! Sprawdź http://www.kursyonline24.eu Więcej informacji o kursach oraz kupony promocyjne!

  algorithms

• Muhammad Sayeed Ghani - YouTube

  https://www.youtube.com/@sghani100/videos

  Videos of my courses taught at UNC and IBA.

  algorithms

• NeetCode

  https://neetcode.io/

  A better way to prepare for coding interviews.

  algorithms

• Problem Solving with Algorithms and Data Structures using Python — Problem Solving with Algorithms and Data Structures

  https://runestone.academy/ns/books/published/pythonds/index.html

  An interactive version of Problem Solving with Algorithms and Data Structures using Python.

  algorithms

• Problem Solving with Algorithms and Data Structures using Python — Problem Solving with Algorithms and Data Structures 3rd edition

  https://runestone.academy/ns/books/published/pythonds3/index.html

  An interactive version of Problem Solving with Algorithms and Data Structures using Python.

  algorithms

• Python for Fun

  https://www.openbookproject.net/py4fun/

  algorithms

• Reducible - YouTube

  https://www.youtube.com/@Reducible/videos

  This channel is all about animating computer science concepts in a fun, interactive, and intuitive manner.

  algorithms

• Static search trees: 40x faster than binary search

  https://curiouscoding.nl/posts/static-search-tree/

  Table of Contents 1 Introduction 1.1 Problem statement 1.2 Motivation 1.3 Recommended reading 1.4 Binary search and Eytzinger layout 1.5 Hugepages 1.6 A note on benchmarking 1.7 Cache lines 1.8 S-trees and B-trees 2 Optimizing find 2.1 Linear 2.2 Auto-vectorization 2.3 Trailing zeros 2.4 Popcount 2.5 Manual SIMD 3 Optimizing the search 3.1 Batching 3.2 Prefetching 3.3 Pointer arithmetic 3.3.1 Up-front splat 3.3.2 Byte-based pointers 3.3.3 The final version 3.4 Skip prefetch 3.5 Interleave 4 Optimizing the tree layout 4.1 Left-tree 4.2 Memory layouts 4.3 Node size \(B=15\) 4.3.1 Data structure size 4.4 Summary 5 Prefix partitioning 5.1 Full layout 5.2 Compact subtrees 5.3 The best of both: compact first level 5.4 Overlapping trees 5.5 Human data 5.6 Prefix map 5.7 Summary 6 Multi-threaded comparison 7 Conclusion 7.1 Future work 7.1.1 Branchy search 7.1.2 Interpolation search 7.1.3 Packing data smaller 7.1.4 Returning indices in original data 7.1.5 Range queries 7.1.6 Sorting queries 7.1.7 Suffix array searching In this post, we will implement a static search tree (S+ tree) for high-throughput searching of sorted data, as introduced on Algorithmica. We’ll mostly take the code presented there as a starting point, and optimize it to its limits. For a large part, I’m simply taking the ‘future work’ ideas of that post and implementing them. And then there will be a bunch of looking at assembly code to shave off all the instructions we can. Lastly, there will be one big addition to optimize throughput: batching.

  algorithms

• The Algorithms

  https://the-algorithms.com/

  Open Source resource for learning Data Structures & Algorithms and their implementation in any Programming Language

  algorithms

• The Algorithms Illuminated Book Series

  https://www.algorithmsilluminated.org/

  algorithms

• The Interactive Handbook on Data Structures and Algorithms

  https://cartesian.app/?utm_source=hackernewsletter&utm_medium=email&utm_term=books

  This one-of-a-kind interactive book offers a hands-on approach to learning data structures and algorithms, featuring rich visualizations, code execution playback, an assortment of problems and an embedded Python environment. It’s designed to support both beginners and more experienced learners through active exploration and interactivity.

  algorithms

• The Ultimate DSA Course for 2025 (with 100% less vibe coding)

  https://www.youtube.com/watch?v=DMeD8trbj6A

  Build data structures from scratch and learn how to think through complex algorithms in Python. Practice your hard problem-solving skills and write faster co...

  algorithms

• Won1samplefinal

  https://theory.stanford.edu/~tim/won1samplefinal.pdf

  algorithms

• a-picture-is-worth-a-1000-words/algorithms at main · girliemac/a-picture-is-worth-a-1000-words

  https://github.com/girliemac/a-picture-is-worth-a-1000-words/tree/main/algorithms

  I am trying to describe complex matters in simple doodles! - girliemac/a-picture-is-worth-a-1000-words

  algorithms

• https://danluu.com/algorithms-interviews/?utm_source=hackernewsletter&utm_medium=email&utm_term=working

  https://danluu.com/algorithms-interviews/?utm_source=hackernewsletter&utm_medium=email&utm_term=working

  algorithms

• visualising data structures and algorithms through animation - VisuAlgo

  https://visualgo.net/en

  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. Together with his students from the National University of Singapore, a series of visualizations were developed and consolidated, from simple sorting algorithms to complex graph data structures. Though specifically designed for the use of NUS students taking various data structure and algorithm classes (CS1010/equivalent, CS2040/equivalent, CS3230, CS3233, and CS4234), as advocators of online learning, we hope that curious minds around the world will find these visualizations useful as well.

  algorithms