أينشتاين مصر (11) || شرح ال Grokking Algorithms - Advanced Big O Notation скачать в хорошем качестве

أينشتاين مصر (11) || شرح ال Grokking Algorithms - Advanced Big O Notation

Welcome to the eleventh video in our "Grokking Algorithms" series on Egypt's Einstein channel! In this episode, we revisit the concept of "Big O Notation" and take a deeper dive into algorithm analysis. This video serves as a continuation of our exploration of Big O Notation, building on the foundation laid in Video 2. 📺 Playlist Link:   • أينشتاين مصر || Grokking Algorithms in Arabic   Big O Notation is a powerful tool for evaluating the efficiency of algorithms, and in this episode, we'll go beyond the basics to understand how to perform a thorough analysis of algorithms. You'll learn how to compare algorithms like Merge Sort and Quicksort, both of which have an average-case time complexity of O(n log n), and answer the question of which one to choose in different scenarios. We'll discuss the nuances of average-case vs. worst-case time complexity, helping you make informed decisions when selecting algorithms for your projects. You'll gain insights into the practical implications of algorithm performance in real-world applications. Throughout the video, we'll explore various examples and scenarios to illustrate the differences between best-case, average-case, and worst-case time complexity, enhancing your algorithmic thinking and problem-solving skills. By the end of this episode, you'll have a solid grasp of Big O Notation and its role in algorithm analysis. You'll be better equipped to choose the most suitable algorithms for specific tasks, taking into consideration their efficiency in different scenarios. Join us in this enlightening exploration of Big O Notation and algorithm analysis, a crucial skill for any programmer or computer science enthusiast. If you find this content valuable, please give it a thumbs up, and don't forget to subscribe to our channel for more captivating episodes. Let's continue our journey through data structures and algorithms together! 🚀 ---------------------------------------------------------------------------------------------- محتوي الفيديو:- 00:00​ - مقدمة قناة أينشتاين مصر 00:07 - Intro about Big O Notation 10:06 - Example to understand the effect of complexity on time 23:25 - Complexity 32:54 - Time Complexity Analysis 39:03 - Frequency Count Method 59:10 - Asymptotic Notation 01:20:47 - The Growth of Functions & Big O Proof 01:34:47 - Useful Rules for Big O 01:39:43 - Big O Sheet Video 01:41:21- Part 1-Big O notation revisited in Grokking Algorithm Book 01:43:12 - Merge Sort 02:18:12 - Part 2-Big O notation revisited in Grokking Algorithm Book 02:44:32 - The End ---------------------------------------------------------------------------------------------- #أينشتاين_مصر #BigONotation #AlgorithmEfficiency #AverageCase #WorstCase #BestCase #GrokkingAlgorithms ╔═.♥. ════════════════════════════════════╗ ＳＵＢＳＣＲＩＢＥ | ＬＩＫＥ | ＣＯＭＭＥＮＴ | ＳＨＡＲＥ | ► Subscribe إشترك ✔    / @einshtenmisr   لاتنسوا الاشتـــــــراك في القنــــاة ✔ ولايـك للفيديو ✔ مشاهدة طيبة أعزائي الكرام ╚══════.♥. ═════════════════════════ #أينشتاين_مصر #Mahmoud_Alyosify https://MahmoudAlyosifySite.github.io/   / einshtenmisr     / mahmoudalyosify   Gmail:mahmoudalyosify@gmail.com Yahoo :mahmoudalyosify@yahoo.com