Algorithms Notes for Beginners and Professionals

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Chapter 1: Getting started with algorithms
Section 1.1: A sample algorithmic problem
Section 1.2: Getting Started with Simple Fizz Buzz Algorithm in Swift

Chapter 2: Algorithm Complexity
Section 2.1: Big-Theta notation
Section 2.2: Comparison of the asymptotic notations
Section 2.3: Big-Omega Notation

Chapter 3: Big-O Notation
Section 3.1: A Simple Loop
Section 3.2: A Nested Loop
Section 3.3: O(log n) types of Algorithms
Section 3.4: An O(log n) example

Chapter 4: Trees
Section 4.1: Typical anary tree representation
Section 4.2: Introduction
Section 4.3: To check if two Binary trees are the same or not

Chapter 5: Binary Search Trees
Section 5.1: Binary Search Tree - Insertion (Python)
Section 5.2: Binary Search Tree - Deletion(C++)
Section 5.3: Lowest common ancestor in a BST
Section 5.4: Binary Search Tree - Python

Chapter 6: Check if a tree is BST or not
Section 6.1: Algorithm to check if a given binary tree is BST
Section 6.2: If a given input tree follows Binary search tree property or not

Chapter 7: Binary Tree traversals
Section 7.1: Level Order traversal - Implementation
Section 7.2: Pre-order, Inorder, and Post Order traversal of a Binary Tree

Chapter 8: Lowest common ancestor of a Binary Tree
Section 8.1: Finding the lowest common ancestor

Chapter 9: Graph
Section 9.1: Storing Graphs (Adjacency Matrix)
Section 9.2: Introduction To Graph Theory
Section 9.3: Storing Graphs (Adjacency List)
Section 9.4: Topological Sort
Section 9.5: Detecting a cycle in a directed graph using Depth First Traversal
Section 9.6: Thorup's algorithm

Chapter 10: Graph Traversals
Section 10.1: Depth First Search traversal function

Chapter 11: Dijkstra’s Algorithm
Section 11.1: Dijkstra's Shortest Path Algorithm

Chapter 12: A* Pathfinding
Section 12.1: Introduction to A*
Section 12.2: A* Pathfinding through a maze with no obstacles
Section 12.3: Solving 8-puzzle problem using A* algorithm

Chapter 13: A* Pathfinding Algorithm
Section 13.1: Simple Example of A* Pathfinding: A maze with no obstacles

Chapter 14: Dynamic Programming
Section 14.1: Edit Distance
Section 14.2: Weighted Job Scheduling Algorithm
Section 14.3: Longest Common Subsequence
Section 14.4: Fibonacci Number
Section 14.5: Longest Common Substring

Chapter 15: Applications of Dynamic Programming
Section 15.1: Fibonacci Numbers

Chapter 16: Kruskal's Algorithm
Section 16.1: Optimal, disjoint-set based implementation
Section 16.2: Simple, more detailed implementation
Section 16.3: Simple, disjoint-set based implementation
Section 16.4: Simple, high level implementation

Chapter 17: Greedy Algorithms
Section 17.1: Huffman Coding
Section 17.2: Activity Selection Problem
Section 17.3: Change-making problem

Chapter 18: Applications of Greedy technique
Section 18.1: Offline Caching
Section 18.2: Ticket automat
Section 18.3: Interval Scheduling
Section 18.4: Minimizing Lateness

Chapter 19: Prim's Algorithm
Section 19.1: Introduction To Prim's Algorithm

Chapter 20: Bellman–Ford Algorithm
Section 20.1: Single Source Shortest Path Algorithm (Given there is a negative cycle in a graph)
Section 20.2: Detecting Negative Cycle in a Graph
Section 20.3: Why do we need to relax all the edges at most (V-1) times

Chapter 21: Line Algorithm
Section 21.1: Bresenham Line Drawing Algorithm

Chapter 22: Floyd-Warshall Algorithm
Section 22.1: All Pair Shortest Path Algorithm

Chapter 23: Catalan Number Algorithm
Section 23.1: Catalan Number Algorithm Basic Information

Chapter 24: Multithreaded Algorithms
Section 24.1: Square matrix multiplication multithread
Section 24.2: Multiplication matrix vector multithread
Section 24.3: merge-sort multithread

Chapter 25: Knuth Morris Pratt (KMP) Algorithm
Section 25.1: KMP-Example

Chapter 26: Edit Distance Dynamic Algorithm
Section 26.1: Minimum Edits required to convert string 1 to string 2

Chapter 27: Online algorithms
Section 27.1: Paging (Online Caching)

Chapter 28: Sorting
Section 28.1: Stability in Sorting

Chapter 29: Bubble Sort
Section 29.1: Bubble Sort
Section 29.2: Implementation in C & C++
Section 29.3: Implementation in C#
Section 29.4: Python Implementation
Section 29.5: Implementation in Java
Section 29.6: Implementation in Javascript

Chapter 30: Merge Sort
Section 30.1: Merge Sort Basics
Section 30.2: Merge Sort Implementation in Go
Section 30.3: Merge Sort Implementation in C & C#
Section 30.4: Merge Sort Implementation in Java
Section 30.5: Merge Sort Implementation in Python
Section 30.6: Bottoms-up Java Implementation

Chapter 31: Insertion Sort
Section 31.1: Haskell Implementation

Chapter 32: Bucket Sort
Section 32.1: C# Implementation

Chapter 33: Quicksort
Section 33.1: Quicksort Basics
Section 33.2: Quicksort in Python
Section 33.3: Lomuto partition java implementation

Chapter 34: Counting Sort
Section 34.1: Counting Sort Basic Information
Section 34.2: Pseudo code Implementation

Chapter 35: Heap Sort
Section 35.1: C# Implementation
Section 35.2: Heap Sort Basic Information

Chapter 36: Cycle Sort
Section 36.1: Pseudo code Implementation

Chapter 37: Odd-Even Sort
Section 37.1: Odd-Even Sort Basic Information

Chapter 38: Selection Sort
Section 38.1: Elixir Implementation
Section 38.2: Selection Sort Basic Information
Section 38.3: Implementation of Selection sort in C#

Chapter 39: Searching
Section 39.1: Binary Search
Section 39.2: Rabin Karp
Section 39.3: Analysis of Linear search (Worst, Average and Best Cases)
Section 39.4: Binary Search: On Sorted Numbers
Section 39.5: Linear search

Chapter 40: Substring Search
Section 40.1: Introduction To Knuth-Morris-Pratt (KMP) Algorithm
Section 40.2: Introduction to Rabin-Karp Algorithm
Section 40.3: Python Implementation of KMP algorithm
Section 40.4: KMP Algorithm in C

Chapter 41: Breadth-First Search
Section 41.1: Finding the Shortest Path from Source to other Nodes
Section 41.2: Finding Shortest Path from Source in a 2D graph
Section 41.3: Connected Components Of Undirected Graph Using BFS

Chapter 42: Depth First Search
Section 42.1: Introduction To Depth-First Search

Chapter 43: Hash Functions
Section 43.1: Hash codes for common types in C#
Section 43.2: Introduction to hash functions

Chapter 44: Travelling Salesman
Section 44.1: Brute Force Algorithm
Section 44.2: Dynamic Programming Algorithm

Chapter 45: Knapsack Problem
Section 45.1: Knapsack Problem Basics
Section 45.2: Solution Implemented in C#

Chapter 46: Equation Solving
Section 46.1: Linear Equation
Section 46.2: Non-Linear Equation

Chapter 47: Longest Common Subsequence
Section 47.1: Longest Common Subsequence Explanation

Chapter 48: Longest Increasing Subsequence
Section 48.1: Longest Increasing Subsequence Basic Information

Chapter 49: Check two strings are anagrams
Section 49.1: Sample input and output
Section 49.2: Generic Code for Anagrams

Chapter 50: Pascal's Triangle
Section 50.1: Pascal triangle in C

Chapter 51: Algo:- Print an m*n matrix in square wise
Section 51.1: Sample Example
Section 51.2: Write the generic code

Chapter 52: Matrix Exponentiation
Section 52.1: Matrix Exponentiation to Solve Example Problems

Chapter 53: Polynomial-time bounded algorithm for Minimum Vertex Cover
Section 53.1: Algorithm Pseudo Code

Chapter 54: Dynamic Time Warping
Section 54.1: Introduction To Dynamic Time Warping

Chapter 55: Fast Fourier Transform
Section 55.1: Radix 2 FFT
Section 55.2: Radix 2 Inverse FFT