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@ -698,7 +698,7 @@ Kodları beyaz tahtaya ya da kağıda yazın, bilgisayara değil.. Örnek girdil
- ### İkili arama ağaçları: BSTs - ### İkili arama ağaçları: BSTs
- [ ] [İkili Arama Ağacı İncelemesi (video)](https://www.youtube.com/watch?v=x6At0nzX92o&index=1&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6) - [ ] [İkili Arama Ağacı İncelemesi (video)](https://www.youtube.com/watch?v=x6At0nzX92o&index=1&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6)
- [ ] [Serieler (video)](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/p82sw/core-introduction-to-binary-search-trees) - [ ] [Serieler (video)](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/p82sw/core-introduction-to-binary-search-trees)
- starts with symbol table and goes through BST applications - sembol tablosuyla başlar ve BST uygulamalarına geçer
- [ ] [Introduction (video)](https://www.coursera.org/learn/data-structures/lecture/E7cXP/introduction) - [ ] [Introduction (video)](https://www.coursera.org/learn/data-structures/lecture/E7cXP/introduction)
- [ ] [MIT (video)](https://www.youtube.com/watch?v=9Jry5-82I68) - [ ] [MIT (video)](https://www.youtube.com/watch?v=9Jry5-82I68)
- C/C++: - C/C++:
@ -712,23 +712,23 @@ Kodları beyaz tahtaya ya da kağıda yazın, bilgisayara değil.. Örnek girdil
- [ ] [Check if a binary tree is binary search tree or not (video)](https://www.youtube.com/watch?v=yEwSGhSsT0U&index=35&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P) - [ ] [Check if a binary tree is binary search tree or not (video)](https://www.youtube.com/watch?v=yEwSGhSsT0U&index=35&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P)
- [ ] [Delete a node from Binary Search Tree (video)](https://www.youtube.com/watch?v=gcULXE7ViZw&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P&index=36) - [ ] [Delete a node from Binary Search Tree (video)](https://www.youtube.com/watch?v=gcULXE7ViZw&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P&index=36)
- [ ] [Inorder Successor in a binary search tree (video)](https://www.youtube.com/watch?v=5cPbNCrdotA&index=37&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P) - [ ] [Inorder Successor in a binary search tree (video)](https://www.youtube.com/watch?v=5cPbNCrdotA&index=37&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P)
- [ ] Implement: - [ ] Uygulama:
- [ ] insert // insert value into tree - [ ] insert // değeri ağaca ekler
- [ ] get_node_count // get count of values stored - [ ] get_node_count // barındırılan düğümlerin sayısını verir
- [ ] print_values // prints the values in the tree, from min to max - [ ] print_values // minimumdan maximuma doğru ağaçtaki değerleri yazdırır
- [ ] delete_tree - [ ] delete_tree
- [ ] is_in_tree // returns true if given value exists in the tree - [ ] is_in_tree // verilen değer ağaçta varsa true döndrür
- [ ] get_height // returns the height in nodes (single node's height is 1) - [ ] get_height // düğümlerin yüksekliğini döndürür (tek düğümlerin yüksekliği: 1)
- [ ] get_min // returns the minimum value stored in the tree - [ ] get_min // ağaçta bulunan minimum değeri verir
- [ ] get_max // returns the maximum value stored in the tree - [ ] get_max // ağaçta bulunan maximum değeri verir
- [ ] is_binary_search_tree - [ ] is_binary_search_tree
- [ ] delete_value - [ ] delete_value
- [ ] get_successor // returns next-highest value in tree after given value, -1 if none - [ ] get_successor // verilen değerden sonra ağaçtaki en yüksek değeri verir, bulunamazsa -1 verir
- ### Heap / Priority Queue / Binary Heap - ### Heap / Öncelik Kuyruğu / Binary Heap
- visualized as a tree, but is usually linear in storage (array, linked list) - ağaç olarak görselleştirilir, ancak depolama ortamında genellikle doğrusaldır (dizi, bağlı liste)
- [ ] [Heap](https://en.wikipedia.org/wiki/Heap_(data_structure)) - [ ] [Heap](https://en.wikipedia.org/wiki/Heap_(data_structure))
- [ ] [Introduction (video)](https://www.coursera.org/learn/data-structures/lecture/2OpTs/introduction) - [ ] [Giriş (video)](https://www.coursera.org/learn/data-structures/lecture/2OpTs/introduction)
- [ ] [Naive Implementations (video)](https://www.coursera.org/learn/data-structures/lecture/z3l9N/naive-implementations) - [ ] [Naive Implementations (video)](https://www.coursera.org/learn/data-structures/lecture/z3l9N/naive-implementations)
- [ ] [Binary Trees (video)](https://www.coursera.org/learn/data-structures/lecture/GRV2q/binary-trees) - [ ] [Binary Trees (video)](https://www.coursera.org/learn/data-structures/lecture/GRV2q/binary-trees)
- [ ] [Tree Height Remark (video)](https://www.coursera.org/learn/data-structures/supplement/S5xxz/tree-height-remark) - [ ] [Tree Height Remark (video)](https://www.coursera.org/learn/data-structures/supplement/S5xxz/tree-height-remark)
@ -741,34 +741,34 @@ Kodları beyaz tahtaya ya da kağıda yazın, bilgisayara değil.. Örnek girdil
- [ ] [MIT: Heaps and Heap Sort (video)](https://www.youtube.com/watch?v=B7hVxCmfPtM&index=4&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb) - [ ] [MIT: Heaps and Heap Sort (video)](https://www.youtube.com/watch?v=B7hVxCmfPtM&index=4&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb)
- [ ] [CS 61B Lecture 24: Priority Queues (video)](https://archive.org/details/ucberkeley_webcast_yIUFT6AKBGE) - [ ] [CS 61B Lecture 24: Priority Queues (video)](https://archive.org/details/ucberkeley_webcast_yIUFT6AKBGE)
- [ ] [Linear Time BuildHeap (max-heap)](https://www.youtube.com/watch?v=MiyLo8adrWw) - [ ] [Linear Time BuildHeap (max-heap)](https://www.youtube.com/watch?v=MiyLo8adrWw)
- [ ] Implement a max-heap: - [ ] Max-heap uygulaması:
- [ ] insert - [ ] insert
- [ ] sift_up - needed for insert - [ ] sift_up - eklemek için gerekli
- [ ] get_max - returns the max item, without removing it - [ ] get_max - maximum öğeyi çıkarmadan return eder
- [ ] get_size() - return number of elements stored - [ ] get_size() - barındırılan eleman sayısını verir
- [ ] is_empty() - returns true if heap contains no elements - [ ] is_empty() - heap eleman içermiyorsa true döndürür
- [ ] extract_max - returns the max item, removing it - [ ] extract_max - maximum öğeyi çıkararak döndürür
- [ ] sift_down - needed for extract_max - [ ] sift_down - extract_max için gerekli
- [ ] remove(i) - removes item at index x - [ ] remove(i) - indexdeki öğeyi kaldırır
- [ ] heapify - create a heap from an array of elements, needed for heap_sort - [ ] heapify - bir dizi öğeden heap oluşturur, heap_sort gerekli
- [ ] heap_sort() - take an unsorted array and turn it into a sorted array in-place using a max heap - [ ] heap_sort() - sıralanmamış bir dizi alır ve max-heap kullanarak sıralı diziye dönüştürür
- note: using a min heap instead would save operations, but double the space needed (cannot do in-place). - not: min-heap kullanmak işlemleri kurtarır, ancak gerekli alan 2 katına çıkacaktır (yerinde yapma).
## Sorting ## Sıralama
- [ ] Notes: - [ ] Notlar:
- Implement sorts & know best case/worst case, average complexity of each: - Sıralamaları uygula & en iyi/en kötü durumu bil, her birinin ortalama karmaşıklığı:
- no bubble sort - it's terrible - O(n^2), except when n <= 16 - bubble sort olmaz - çok kötü - O(n^2), n <= 16 hariç
- [ ] stability in sorting algorithms ("Is Quicksort stable?") - [ ] sıralama algoritmalarında stabilite ("Quicksort stabil mi?")
- [Sorting Algorithm Stability](https://en.wikipedia.org/wiki/Sorting_algorithm#Stability) - [Sorting Algorithm Stability](https://en.wikipedia.org/wiki/Sorting_algorithm#Stability)
- [Stability In Sorting Algorithms](http://stackoverflow.com/questions/1517793/stability-in-sorting-algorithms) - [Stability In Sorting Algorithms](http://stackoverflow.com/questions/1517793/stability-in-sorting-algorithms)
- [Stability In Sorting Algorithms](http://www.geeksforgeeks.org/stability-in-sorting-algorithms/) - [Stability In Sorting Algorithms](http://www.geeksforgeeks.org/stability-in-sorting-algorithms/)
- [Sorting Algorithms - Stability](http://homepages.math.uic.edu/~leon/cs-mcs401-s08/handouts/stability.pdf) - [Sorting Algorithms - Stability](http://homepages.math.uic.edu/~leon/cs-mcs401-s08/handouts/stability.pdf)
- [ ] Which algorithms can be used on linked lists? Which on arrays? Which on both? - [ ] Hangi algoritmalar bağlı listelerde kullanılabilir? Hangileri dizilerde? Hangileri hepsinde?
- I wouldn't recommend sorting a linked list, but merge sort is doable. - Bağlı listeyi sıralamanızı tavsiye etmem, ancak merge sort bunu yapabilir.
- [Merge Sort For Linked List](http://www.geeksforgeeks.org/merge-sort-for-linked-list/) - [Merge Sort For Linked List](http://www.geeksforgeeks.org/merge-sort-for-linked-list/)
- For heapsort, see Heap data structure above. Heap sort is great, but not stable. - Heap sort için, yukarıdaki Heap veri yapısına bakın. Heap sort güzel, ama stabil değil.
- [ ] [Sedgewick - Mergesort (5 videos)](https://www.youtube.com/watch?v=4nKwesx_c8E&list=PLe-ggMe31CTeunC6GZHFBmQx7EKtjbGf9) - [ ] [Sedgewick - Mergesort (5 videos)](https://www.youtube.com/watch?v=4nKwesx_c8E&list=PLe-ggMe31CTeunC6GZHFBmQx7EKtjbGf9)
- [ ] [1. Mergesort](https://www.youtube.com/watch?v=4nKwesx_c8E&list=PLe-ggMe31CTeunC6GZHFBmQx7EKtjbGf9&index=1) - [ ] [1. Mergesort](https://www.youtube.com/watch?v=4nKwesx_c8E&list=PLe-ggMe31CTeunC6GZHFBmQx7EKtjbGf9&index=1)
@ -797,22 +797,22 @@ Kodları beyaz tahtaya ya da kağıda yazın, bilgisayara değil.. Örnek girdil
- [ ] [Quicksort (video)](https://www.youtube.com/watch?v=y_G9BkAm6B8&index=4&list=PL89B61F78B552C1AB) - [ ] [Quicksort (video)](https://www.youtube.com/watch?v=y_G9BkAm6B8&index=4&list=PL89B61F78B552C1AB)
- [ ] [Selection Sort (video)](https://www.youtube.com/watch?v=6nDMgr0-Yyo&index=8&list=PL89B61F78B552C1AB) - [ ] [Selection Sort (video)](https://www.youtube.com/watch?v=6nDMgr0-Yyo&index=8&list=PL89B61F78B552C1AB)
- [ ] Merge sort code: - [ ] Merge sort kod:
- [ ] [Using output array (C)](http://www.cs.yale.edu/homes/aspnes/classes/223/examples/sorting/mergesort.c) - [ ] [Using output array (C)](http://www.cs.yale.edu/homes/aspnes/classes/223/examples/sorting/mergesort.c)
- [ ] [Using output array (Python)](https://github.com/jwasham/practice-python/blob/master/merge_sort/merge_sort.py) - [ ] [Using output array (Python)](https://github.com/jwasham/practice-python/blob/master/merge_sort/merge_sort.py)
- [ ] [In-place (C++)](https://github.com/jwasham/practice-cpp/blob/master/merge_sort/merge_sort.cc) - [ ] [In-place (C++)](https://github.com/jwasham/practice-cpp/blob/master/merge_sort/merge_sort.cc)
- [ ] Quick sort code: - [ ] Quick sort kod:
- [ ] [Implementation (C)](http://www.cs.yale.edu/homes/aspnes/classes/223/examples/randomization/quick.c) - [ ] [Implementation (C)](http://www.cs.yale.edu/homes/aspnes/classes/223/examples/randomization/quick.c)
- [ ] [Implementation (C)](https://github.com/jwasham/practice-c/blob/master/quick_sort/quick_sort.c) - [ ] [Implementation (C)](https://github.com/jwasham/practice-c/blob/master/quick_sort/quick_sort.c)
- [ ] [Implementation (Python)](https://github.com/jwasham/practice-python/blob/master/quick_sort/quick_sort.py) - [ ] [Implementation (Python)](https://github.com/jwasham/practice-python/blob/master/quick_sort/quick_sort.py)
- [ ] Implement: - [ ] Uygulama:
- [ ] Mergesort: O(n log n) average and worst case - [ ] Mergesort: O(n log n) ortalama ve en kötü durum
- [ ] Quicksort O(n log n) average case - [ ] Quicksort O(n log n) ortalama durum
- Selection sort and insertion sort are both O(n^2) average and worst case - Selection sort ve insertion sort her ikisi de O(n^2) ortalama ve en kötü durum
- For heapsort, see Heap data structure above. - Heapsort için, yukarıdaki Heap veri yapısına bakın.
- [ ] Not required, but I recommended them: - [ ] Gerekli değil, fakat tavsiye ediyorum:
- [ ] [Sedgewick - Radix Sorts (6 videos)](https://www.youtube.com/playlist?list=PLe-ggMe31CTcNvUX9E3tQeM6ntrdR8e53) - [ ] [Sedgewick - Radix Sorts (6 videos)](https://www.youtube.com/playlist?list=PLe-ggMe31CTcNvUX9E3tQeM6ntrdR8e53)
- [ ] [1. Strings in Java](https://www.youtube.com/watch?v=zRzU-FWsjNU&list=PLe-ggMe31CTcNvUX9E3tQeM6ntrdR8e53&index=6) - [ ] [1. Strings in Java](https://www.youtube.com/watch?v=zRzU-FWsjNU&list=PLe-ggMe31CTcNvUX9E3tQeM6ntrdR8e53&index=6)
- [ ] [2. Key Indexed Counting](https://www.youtube.com/watch?v=CtgKYmXs62w&list=PLe-ggMe31CTcNvUX9E3tQeM6ntrdR8e53&index=5) - [ ] [2. Key Indexed Counting](https://www.youtube.com/watch?v=CtgKYmXs62w&list=PLe-ggMe31CTcNvUX9E3tQeM6ntrdR8e53&index=5)
@ -826,24 +826,24 @@ Kodları beyaz tahtaya ya da kağıda yazın, bilgisayara değil.. Örnek girdil
- [ ] [Randomization: Matrix Multiply, Quicksort, Freivalds' algorithm (video)](https://www.youtube.com/watch?v=cNB2lADK3_s&index=8&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp) - [ ] [Randomization: Matrix Multiply, Quicksort, Freivalds' algorithm (video)](https://www.youtube.com/watch?v=cNB2lADK3_s&index=8&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp)
- [ ] [Sorting in Linear Time (video)](https://www.youtube.com/watch?v=pOKy3RZbSws&list=PLUl4u3cNGP61hsJNdULdudlRL493b-XZf&index=14) - [ ] [Sorting in Linear Time (video)](https://www.youtube.com/watch?v=pOKy3RZbSws&list=PLUl4u3cNGP61hsJNdULdudlRL493b-XZf&index=14)
As a summary, here is a visual representation of [15 sorting algorithms](https://www.youtube.com/watch?v=kPRA0W1kECg). Özetlemek gerekirse, burada [15 sıralama algoritmasının](https://www.youtube.com/watch?v=kPRA0W1kECg) görsel temsili var.
If you need more detail on this subject, see "Sorting" section in [Additional Detail on Some Subjects](#additional-detail-on-some-subjects) Bu konuda daha fazla bilgiye ihtiyacınız varsa, "Sıralama" bölümüne bakın [Bazı Konularda Ek Bilgiler](#additional-detail-on-some-subjects)
## Graphs ## Graflar
Graphs can be used to represent many problems in computer science, so this section is long, like trees and sorting were. Graflar, bilgisayar bilimlerinde birçok sorunu temsil etmek için kullanılabilir, bu nedenle bu bölüm ağaçlar ve sıralama algoritmaları gibi uzundur.
- Notes: - Notlar:
- There are 4 basic ways to represent a graph in memory: - Grafı bellekte temsil etmek için 4 temel yol vardır:
- objects and pointers - objeler ve işaretçiler
- adjacency matrix - bitişiklik matrisi
- adjacency list - bitişik liste
- adjacency map - bitişik map
- Familiarize yourself with each representation and its pros & cons - Her temsilciliği ve artılarını - eksilerini tanıyın.
- BFS and DFS - know their computational complexity, their tradeoffs, and how to implement them in real code - BFS ve DFS - hesaplama karmaşıklığını bilin, ödün vermelerini verin, gerçek kod uygulamasını bilin.
- When asked a question, look for a graph-based solution first, then move on if none. - Bir soru sorulduğunda önce graf tabanlı bir çözüm arayın, eğer yoksa devam edin.
- [ ] Skiena Lectures - great intro: - [ ] Skiena Dersleri - güzel giriş:
- [ ] [CSE373 2012 - Lecture 11 - Graph Data Structures (video)](https://www.youtube.com/watch?v=OiXxhDrFruw&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&index=11) - [ ] [CSE373 2012 - Lecture 11 - Graph Data Structures (video)](https://www.youtube.com/watch?v=OiXxhDrFruw&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&index=11)
- [ ] [CSE373 2012 - Lecture 12 - Breadth-First Search (video)](https://www.youtube.com/watch?v=g5vF8jscteo&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&index=12) - [ ] [CSE373 2012 - Lecture 12 - Breadth-First Search (video)](https://www.youtube.com/watch?v=g5vF8jscteo&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&index=12)
- [ ] [CSE373 2012 - Lecture 13 - Graph Algorithms (video)](https://www.youtube.com/watch?v=S23W6eTcqdY&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&index=13) - [ ] [CSE373 2012 - Lecture 13 - Graph Algorithms (video)](https://www.youtube.com/watch?v=S23W6eTcqdY&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&index=13)
@ -851,7 +851,7 @@ Graphs can be used to represent many problems in computer science, so this secti
- [ ] [CSE373 2012 - Lecture 15 - Graph Algorithms (con't 2) (video)](https://www.youtube.com/watch?v=ia1L30l7OIg&index=15&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b) - [ ] [CSE373 2012 - Lecture 15 - Graph Algorithms (con't 2) (video)](https://www.youtube.com/watch?v=ia1L30l7OIg&index=15&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b)
- [ ] [CSE373 2012 - Lecture 16 - Graph Algorithms (con't 3) (video)](https://www.youtube.com/watch?v=jgDOQq6iWy8&index=16&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b) - [ ] [CSE373 2012 - Lecture 16 - Graph Algorithms (con't 3) (video)](https://www.youtube.com/watch?v=jgDOQq6iWy8&index=16&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b)
- [ ] Graphs (review and more): - [ ] Graflar (inceleme ve fazlası):
- [ ] [6.006 Single-Source Shortest Paths Problem (video)](https://www.youtube.com/watch?v=Aa2sqUhIn-E&index=15&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb) - [ ] [6.006 Single-Source Shortest Paths Problem (video)](https://www.youtube.com/watch?v=Aa2sqUhIn-E&index=15&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb)
- [ ] [6.006 Dijkstra (video)](https://www.youtube.com/watch?v=2E7MmKv0Y24&index=16&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb) - [ ] [6.006 Dijkstra (video)](https://www.youtube.com/watch?v=2E7MmKv0Y24&index=16&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb)
@ -866,41 +866,41 @@ Graphs can be used to represent many problems in computer science, so this secti
- [ ] [Greedy Algorithms: Minimum Spanning Tree (video)](https://www.youtube.com/watch?v=tKwnms5iRBU&index=16&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp) - [ ] [Greedy Algorithms: Minimum Spanning Tree (video)](https://www.youtube.com/watch?v=tKwnms5iRBU&index=16&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp)
- [ ] [Strongly Connected Components Kosaraju's Algorithm Graph Algorithm (video)](https://www.youtube.com/watch?v=RpgcYiky7uw) - [ ] [Strongly Connected Components Kosaraju's Algorithm Graph Algorithm (video)](https://www.youtube.com/watch?v=RpgcYiky7uw)
- Full Coursera Course: - Full Coursera Kursu:
- [ ] [Algorithms on Graphs (video)](https://www.coursera.org/learn/algorithms-on-graphs/home/welcome) - [ ] [Algorithms on Graphs (video)](https://www.coursera.org/learn/algorithms-on-graphs/home/welcome)
- I'll implement: - Bunları uygulayacağım:
- [ ] DFS with adjacency list (recursive) - [ ] DFS ile bitişik liste (rekürsif)
- [ ] DFS with adjacency list (iterative with stack) - [ ] DFS ile bitişik liste (yığınla iteratif)
- [ ] DFS with adjacency matrix (recursive) - [ ] DFS ile bitişik matris (rekürsif)
- [ ] DFS with adjacency matrix (iterative with stack) - [ ] DFS ile bitişik matris (yığınla iteratif)
- [ ] BFS with adjacency list - [ ] BFS ile bitişik liste
- [ ] BFS with adjacency matrix - [ ] BFS ile bitişik matris
- [ ] single-source shortest path (Dijkstra) - [ ] tek kaynak en kısa yol (Dijkstra)
- [ ] minimum spanning tree - [ ] minimum yayılan ağaç
- DFS-based algorithms (see Aduni videos above): - DFS-tabanlı algoritmalar (yukarıdaki Aduni videolarına bakın):
- [ ] check for cycle (needed for topological sort, since we'll check for cycle before starting) - [ ] döngüye bak (topolojik sıralama için gerekli, başlamadan önce döngüyü konyrol edeceğiz)
- [ ] topological sort - [ ] topolojik sıralama
- [ ] count connected components in a graph - [ ] bir graftaki bağlı komponentleri saymak
- [ ] list strongly connected components - [ ] kuvvetli bağlı komponentleri listele
- [ ] check for bipartite graph - [ ] iki parçalı graf için kontrol et
You'll get more graph practice in Skiena's book (see Books section below) and the interview books Skienna'nın kitabında (aşağıdaki Kitaplar bölümüne bakın) ve mülakat kitaplarında daha fazla graf pratiği bulabilirsiniz.
## Even More Knowledge ## Daha Fazla Bilgi
- ### Recursion - ### Recursif
- [ ] Stanford lectures on recursion & backtracking: - [ ] Stanford dersleri rekürsif & geri yineleme:
- [ ] [Lecture 8 | Programming Abstractions (video)](https://www.youtube.com/watch?v=gl3emqCuueQ&list=PLFE6E58F856038C69&index=8) - [ ] [Lecture 8 | Programming Abstractions (video)](https://www.youtube.com/watch?v=gl3emqCuueQ&list=PLFE6E58F856038C69&index=8)
- [ ] [Lecture 9 | Programming Abstractions (video)](https://www.youtube.com/watch?v=uFJhEPrbycQ&list=PLFE6E58F856038C69&index=9) - [ ] [Lecture 9 | Programming Abstractions (video)](https://www.youtube.com/watch?v=uFJhEPrbycQ&list=PLFE6E58F856038C69&index=9)
- [ ] [Lecture 10 | Programming Abstractions (video)](https://www.youtube.com/watch?v=NdF1QDTRkck&index=10&list=PLFE6E58F856038C69) - [ ] [Lecture 10 | Programming Abstractions (video)](https://www.youtube.com/watch?v=NdF1QDTRkck&index=10&list=PLFE6E58F856038C69)
- [ ] [Lecture 11 | Programming Abstractions (video)](https://www.youtube.com/watch?v=p-gpaIGRCQI&list=PLFE6E58F856038C69&index=11) - [ ] [Lecture 11 | Programming Abstractions (video)](https://www.youtube.com/watch?v=p-gpaIGRCQI&list=PLFE6E58F856038C69&index=11)
- when it is appropriate to use it - onu kullanmak uygun olduğunda
- how is tail recursion better than not? - kuyruk yenilemesi daha iyi değil mi?
- [ ] [What Is Tail Recursion Why Is It So Bad?](https://www.quora.com/What-is-tail-recursion-Why-is-it-so-bad) - [ ] [What Is Tail Recursion Why Is It So Bad?](https://www.quora.com/What-is-tail-recursion-Why-is-it-so-bad)
- [ ] [Tail Recursion (video)](https://www.youtube.com/watch?v=L1jjXGfxozc) - [ ] [Tail Recursion (video)](https://www.youtube.com/watch?v=L1jjXGfxozc)
- ### Dynamic Programming - ### Dinamik Programlama
- This subject can be pretty difficult, as each DP soluble problem must be defined as a recursion relation, and coming up with it can be tricky. - This subject can be pretty difficult, as each DP soluble problem must be defined as a recursion relation, and coming up with it can be tricky.
- I suggest looking at many examples of DP problems until you have a solid understanding of the pattern involved. - I suggest looking at many examples of DP problems until you have a solid understanding of the pattern involved.
- [ ] Videos: - [ ] Videos: