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Greedy Algorithms using Python
course content

Course Content

Greedy Algorithms using Python

Greedy Algorithms using Python

1. Greedy Algorithms: Overview and Examples
Why Greedy?Description and Simple ExampleSchedule ProblemEuclidean AlgorithmEgyptian Fraction ProblemJob Sequencing Problem
2. Greedy on Arrays
Make Arrays EqualMinimum Product SubsetJumping Frog
3. Greedy on Graphs
PreparationDijkstra Shortest Path AlgorithmKruskal’s MSTPrim's MST

bookPrim's MST

This algorithm is another one approach to find the MST - minimum spanning tree. The main idea is to partition a set of vertices into two: included to MST already and excluded. Step by step you’ll replace vertices from the second set to the first by picking the less weighted edge that connects both sets.

So algorithm is next:

  1. Put the start vertex to the visited, the rest will be unvisited, i. e. in the second set.
  2. Start adding vertices. Visit all neighbors for all visited vertices and select the edge with least weight, that does not create a cycle. Mark the adjacent vertex as visited.
  3. Do the 2) until all vertices are visited.

You can find a lot of different implementations, but the main idea is to put all vertices into the visited set step by step.

Task

Complete the primMST() algorithm inside Graph class. Init the graph and call this method. To detect a cycle, use BFS() or DFS() algorithms. You can implement it inside the class.

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Section 3. Chapter 4
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bookPrim's MST

This algorithm is another one approach to find the MST - minimum spanning tree. The main idea is to partition a set of vertices into two: included to MST already and excluded. Step by step you’ll replace vertices from the second set to the first by picking the less weighted edge that connects both sets.

So algorithm is next:

  1. Put the start vertex to the visited, the rest will be unvisited, i. e. in the second set.
  2. Start adding vertices. Visit all neighbors for all visited vertices and select the edge with least weight, that does not create a cycle. Mark the adjacent vertex as visited.
  3. Do the 2) until all vertices are visited.

You can find a lot of different implementations, but the main idea is to put all vertices into the visited set step by step.

Task

Complete the primMST() algorithm inside Graph class. Init the graph and call this method. To detect a cycle, use BFS() or DFS() algorithms. You can implement it inside the class.

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Everything was clear?

How can we improve it?

Thanks for your feedback!

Section 3. Chapter 4
toggle bottom row

bookPrim's MST

This algorithm is another one approach to find the MST - minimum spanning tree. The main idea is to partition a set of vertices into two: included to MST already and excluded. Step by step you’ll replace vertices from the second set to the first by picking the less weighted edge that connects both sets.

So algorithm is next:

  1. Put the start vertex to the visited, the rest will be unvisited, i. e. in the second set.
  2. Start adding vertices. Visit all neighbors for all visited vertices and select the edge with least weight, that does not create a cycle. Mark the adjacent vertex as visited.
  3. Do the 2) until all vertices are visited.

You can find a lot of different implementations, but the main idea is to put all vertices into the visited set step by step.

Task

Complete the primMST() algorithm inside Graph class. Init the graph and call this method. To detect a cycle, use BFS() or DFS() algorithms. You can implement it inside the class.

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Everything was clear?

How can we improve it?

Thanks for your feedback!

This algorithm is another one approach to find the MST - minimum spanning tree. The main idea is to partition a set of vertices into two: included to MST already and excluded. Step by step you’ll replace vertices from the second set to the first by picking the less weighted edge that connects both sets.

So algorithm is next:

  1. Put the start vertex to the visited, the rest will be unvisited, i. e. in the second set.
  2. Start adding vertices. Visit all neighbors for all visited vertices and select the edge with least weight, that does not create a cycle. Mark the adjacent vertex as visited.
  3. Do the 2) until all vertices are visited.

You can find a lot of different implementations, but the main idea is to put all vertices into the visited set step by step.

Task

Complete the primMST() algorithm inside Graph class. Init the graph and call this method. To detect a cycle, use BFS() or DFS() algorithms. You can implement it inside the class.

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Section 3. Chapter 4
Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
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