Coding interview preparation

The code on this repo has been inspired by those repositories:

• https://github.com/keon/algorithms
• https://github.com/eriklindernoren/ML-From-Scratch
• https://github.com/w-hat/ctci-solutions

I have added test function for each elements in order to test the code and make sure everything is correct.

Includes in code_prep

• Abstract Structures (22)

  • Arrays (7)

    • delete_nth
    • flatten
    • garage
    • josephus_problem
    • longest_non_repeat
    • merge_intervals
    • remove_duplicates

  • Linked List (7)

    • Base
    • Is Circular
    • Double Linked List
    • Part Linked List
    • Sum Linked Lists
    • Intersections

  • Heap (4)

    • heap
    • find N largest items seq
    • Merge Sorted Seqs
    • Priority Queue

  • Queue and Stack (5)

    • queue
    • animal shelter
    • linked Queue
    • Stack with Min
    • Stack of Plates

• Short Phone Interviews Problem (34)

  • balanced
  • binary search
  • breadth search first : bst
  • check anagrams
  • combinaison
  • find_0_MN_replace_cols_rows
  • find_3_numbers
  • hast table
  • is_tree_balanced
  • linked list
  • longest commong substring
  • longest increasing subsequence
  • palindrom
  • permutation
  • queue
  • stack
  • tree
    • add
    • search
    • print tree
    • preorder
    • inorder
    • postorder
  • Binary Search Matrix
  • Routes Between Nodes
  • BasketBall
  • Coins
  • Virtual Coins
  • Permutations without dups
  • Tower of Hanoi
  • PGCD
    • pgcd
    • pgcdn
    • pgcde
    • ppcm
    • ppcmn
  • Operations
    • Substract
    • Recursive Multiply
    • Divide
  • Living People

• Bit Manipulation (4)

  • Inserstion
  • Power of two
  • Russian Peasant Multiplication
  • Number Max

• Sort And Searching (10)

  • Sort (7)

    • Quick Sort
    • Bubble Sort
    • Merge Sort
    • Count Sort
    • Gnome Sort
    • Heap Sort
    • Sort Peaks and Valleys

  • Searching (3)

    • rotated_search
    • sorted_search_no_size
    • sparse_search

• Advanced (3)

  • Dijkstra
  • Newton Method
  • Kruskal

• Machine Learning from scratch (12)

  • Supervised (7)

    • Decision Tree
    • Knn
    • SVM ( Bugs in original version )
    • Naive Bayesn
    • LDA
    • One vs One:
      • SVM
    • Adaboost ( Simulation )

  • Unsupervised (3)

    • Kmeans
    • PCA
    • Gaussian Mixture

  • Utils (2)

    • kernels
    • operations

Greetings

Thanks to

• eriklindernore
• keon

for their great code examples which I used to inspire myself