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A "blindcuber" is someone who solves a Rubik's Cube or similar puzzles while blindfolded, relying on memory and algorithms to manipulate the pieces. They may use tactile markings or specific algorithms to navigate the cube's faces.

103,003 Aufrufe • vor 1 Jahr •via X (Twitter)

9 Kommentare

Profilbild von Dandy Peter
Dandy Petervor 1 Jahr

Rubiks

Profilbild von Gemini
Geminivor 1 Jahr

Gemini is the simple and secure way to buy crypto.

Profilbild von Chespie.ape 👽🧑‍🚀💩🍌🦍
Chespie.ape 👽🧑‍🚀💩🍌🦍vor 1 Jahr

Humans name this game

Profilbild von @Riemerville
@Riemervillevor 1 Jahr

it’s specific algorithms

Profilbild von Ayça's
Ayça'svor 1 Jahr

NİCE

Profilbild von Uğur
Uğurvor 1 Jahr

🦶

Profilbild von Mo Toldya
Mo Toldyavor 1 Jahr

cheating w a band aid cam.

Profilbild von Diana Dee Jarvis
Diana Dee Jarvisvor 1 Jahr

Or they're peeking over the top of the mask.

Profilbild von Spurius Larcius Celsus Germanicus
Spurius Larcius Celsus Germanicusvor 1 Jahr

Isn’t that cheating? “Bending”the corner cube?

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25 algorithms every programmer should know: Let's start with my top favorite 10. If nothing else, you should read about these algorithms and have a good idea of how they work: 1. Linear search to find an element in a list 2. Binary search to find an element on a sorted list 3. Bubble sort to sort a list 4. Merge sort will also sort lists 5. Quicksort to sort the list and do it fast 6. Dijkstra to find the shortest path in a graph 7. Breadth-first Search (BFS) for trees or graphs 8. Depth-first search (DFS) for trees or graphs 9. Huffman for doing data compression 10. Anything related to dynamic programming Learning about algorithms is like getting tattoos: you never have enough. Here are another 5 algorithms that will help you go beyond the basics: 11. Kruskal for the finding minimum spanning tree 12. Floyd Warshall, shortest paths in a graph 13. Union Find to detect cycles in a graph 14. Bellman-Ford, shortest path in a graph 15. Lee for finding the shortest path in a maze If you are serious about this topic, I recommend learning about algorithms' space and time complexity. People usually refer to this topic as "Big O" notation. You should build a good intuition about the performance of different algorithms and learn how to evaluate them. Machine Learning will rule the next 50 years, so the next 10 algorithms you can't ignore are the following: 16. Linear Regression 17. Logistic Regression 18. Decision Trees 19. Bayes' theorem 20. k-Nearest Neighbors (kNN) 21. Every algorithm related to neural networks 22. K-means 23. Random forest 24. Gradient boosting algorithms 25. Any dimensionality reduction algorithm (PCA, for instance) There are many more mind-blowing algorithms! I haven't found a better way to understand how computers work from a first-principles point of view than reading about different algorithms. Take a look at the attached video.

Santiago

273,905 Aufrufe • vor 2 Jahren