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YOWatch how Heap Sort turns a messy array into a perfectly sorted one. β‘
Algorithms become easy when you see them in action.
@youcancodeit
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YOHeap Sort is a comparison-based sorting algorithm based on the Binary Heap data structure.
It is an optimized version of selection sort.
The algorithm repeatedly finds the maximum (or minimum) element and swaps it with the last (or first) element.
Using a binary heap allows efficient access to the max (or min) element in O(log n) time instead of O(n).
The process is repeated for the remaining elements until the array is sorted.
Overall, Heap Sort achieves a time complexity of O(n log n).
#programming #softwareengineer #coding #dsa #algorrithms
@yo07_dev
6.4K
REHeap Sort is a comparison-based sorting algorithm based on the Binary Heap data structure. It is an optimized version of selection sort. The algorithm repeatedly finds the maximum (or minimum) element and swaps it with the last (or first) element. Using a binary heap allows efficient access to the max (or min) element in O(log n) time instead of O(n). The process is repeated for the remaining elements until the array is sorted. Overall, Heap Sort achieves a time complexity of O(n log n). #softwareengineer #datastructures #coding #algorithms #programming
@real_kingsleymayor
142
PRHow to Avoid OFFSET Pagination Slowing to a Crawl
High OFFSET forces MySQL to scan tons of rows.
#mysql #pagination #offset #performance #howto #scaling
@precisionsql
844
18
_PFor-Enumerate-MOVING ZEROS TO THE END OF THE LIST
@_python_z
240
LAQuickSort visualized in real-time π₯
120 bars. One algorithm. Pure satisfaction.
120κ° λ§λ. νλμ μκ³ λ¦¬μ¦. μ λ ¬λλ μκ°μ μΎκ°.
μ½λκ° μ€μ€λ‘ νμ΄νλλ κ±Έ μ§μΌλ³΄μΈμ.
Watch the code write itself while the sort runs.
#coding #programming #quicksort #algorithm #visualization #developer #codeart #satisfying #tech #p5js
@layeredlabs_
179
YNmix of examples from the Strudel page using vim as the text editor and cava as the visualizer.
@ynwrdcreso
24.6K
EMLearn about bloom filters. These wonderful, probabilistic data structures can be used to filter out items which are not in your set. They consist of an array of bits of length m.
To insert each item, compute k hashes mod m, and set the bits at these indexes to 1. Then to check if an item exists in your set, compute the same k hashes mod m. If any of these bits are 0, the item definitely does not exist in your set, because if it did it would set all these bits to 1 during insertion.
The trade-off is false positives - if all the candidate bits of the item you are checking are 1, the item may or may not be in the set. You don't know for sure because a combination of other elements' insertions could have also set those bits to 1.
Therefore it is most useful for applications where it acts like a filter, to filter out items which are not in the set and save more expensive lookups. This is due to its awesome time and space benefits thanks to not having to store all the items themselves!
@emcapsulation
186
BUJo sahi answer dega uska naam next reel me mention hoga! π
#javascript
#tradinglife
#stockmarketindia
#codingchallenge
#learncoding
@build_web_pages
2.8K
THO(n log n) isnβt just a complexityβitβs a masterpiece. π
βWhile other algorithms struggle with scale, Merge Sort uses the ultimate "Divide and Conquer" strategy to bring order to chaos.
βThis is exactly how recursion looks when itβs optimized. Notice how the array splits to its core and merges back stronger.
βIs this the GOAT of sorting algorithms? Letβs argue in the comments. π
β#VectorForge #MergeSort #SoftwareEngineering #FAANG #CodingInterview
@thevectorforge
84
VIDay 4 of SkillUp Series #sql
@vikashabhishek123
β¨ #Minheap Discovery Guide
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