algorithms-specialization-notebook

My notes and assignments for Stanfords "Algorithms Specialization" class on Coursera

There are 4 courses (quarters from the corresponding university course). Each have 4 week-long sections

Implementations

Course 1 - Divide and Conquer, Sorting and Searching, and Randomized Algorithms

Karatsuba Multiplication

Inversion Counter

Strassen's Subcubic Matrix Multiplication

Randomized Selection

Randomized Contraction

Course 2 - Graph Search, Shortest Paths, and Data Structures

Breadth First Search

Undirected Connectivity

Kosaraju Two Pass and Depth First Search

Dijkstra's Shortest Path

Median Maintenance

Two Sum via Hash Map

Course 3 - Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming

Job Scheduling and minimize weighted sum of completion times

Prim's minimum spanning tree

Max-Spacing k-clusterings via kruskal's algorithm

Huffman optimal binary prefix-free encoding

Max weight independent set of a path graph

Knapsack problem

Course 4 - Shortest Paths Revisited, NP-Complete Problems and What To Do About Them

Traveling Salesman Problem