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Graph theory algorithms visualized

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Added 3 years ago by tutsnode in Other
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Graph theory algorithms visualized (Size: 3.1 GB)
  0 0 B
  1. Adjacency list representation.mp4 62.2 MB
  1. Adjacency list representation.srt 13.8 KB
  1. Depth-first search (DFS) algorithm.mp4 93.2 MB
  1. Depth-first search (DFS) algorithm.srt 24 KB
  1. Introduction to graph theory.mp4 45.5 MB
  1. Introduction to graph theory.srt 7.1 KB
  1. Introduction.srt 4.4 KB
  1 155 KB
  1. Introduction to graph coloring.mp4 96.7 MB
  1. Introduction to graph coloring.srt 17.4 KB
  1. Introduction.mp4 29.4 MB
  1. What is a (minimum) spanning tree.mp4 55.3 MB
  1. What is a (minimum) spanning tree.srt 10.3 KB
  1. What is a Eulerian pathcycle.mp4 89.4 MB
  1. What is a Eulerian pathcycle.srt 10.6 KB
  1. What is a tree.mp4 82.1 MB
  1. What is a tree.srt 14.1 KB
  1. What is topological sort.mp4 58.9 MB
  1. What is topological sort.srt 10.9 KB
  1.1 adjacency list.pptx 890.5 KB
  1.1 depth-first search.pptx 1.5 MB
  1.1 eulerian trail intro.pptx 1.6 MB
  1.1 find_spanning_tree.py 1.6 KB
  1.1 graph coloring.pptx 2.8 MB
  1.1 introduction.pptx 2.3 MB
  1.1 is_tree.py 1.8 KB
  1.1 shortest path intro.pptx 1.2 MB
  1.1 topological sort intro.pptx 808.3 KB
  1.2 FindSpanningTree.java 2.4 KB
  1.2 IsTree.java 3.5 KB
  1.2 dfs_visualization.py 2.8 KB
  1.2 graph_adj_list.py 2.8 KB
  1.3 Dfs.java 1.9 KB
  1.3 GraphAdjList.java 3.5 KB
  1.3 mst-intro.pptx 1 MB
  1.3 trees introduction.pptx 1.6 MB
  1.4 dfs.py 1.2 KB
  2. Adjacency matrix representation.mp4 47.6 MB
  2. Adjacency matrix representation.srt 9.1 KB
  2. Checking 2-colorability (bipartite graph).mp4 44.1 MB
  2. Checking 2-colorability (bipartite graph).srt 11.6 KB
  2. DFS-based topological sort algorithm.mp4 86.3 MB
  2. DFS-based topological sort algorithm.srt 18.8 KB
  2. Dijkstra's algorithm.mp4 213.5 MB
  2. Dijkstra's algorithm.srt 49.8 KB
  2. Hierholzer's algorithm.mp4 94 MB
  2. Out-trees (arborescence) and graph to out-tree conversion.srt 7.8 KB
  2. Prim's algorithm.mp4 124.3 MB
  2. Prim's algorithm.srt 26.5 KB
  2. Problem Path exists in a graph.html 1.3 KB
  2 145.9 KB
  2. Hierholzer's algorithm.srt 22.5 KB
  2. Out-trees (arborescence) and graph to out-tree conversion.mp4 41 MB
  2. [IMPORTANT] Before we start.html 2.8 KB
  2.1 Binary heaps YouTube video.html 102.4 B
  2.1 FibonacciHeap.java 23.8 KB
  2.1 Hierholzer.java 2.9 KB
  2.1 adjacency matrix.pptx 1 MB
  2.1 graph to out-tree.pptx 922.8 KB
  2.1 is bipartite.pptx 759.7 KB
  2.1 topological sort dfs.pptx 1.3 MB
  2.2 Dijkstra.java 3.8 KB
  2.2 Prim.java 3.5 KB
  2.2 graph_adj_mat.py 4 KB
  2.2 hierholzer.pptx 1.4 MB
  2.2 to_out_tree.py 1.3 KB
  2.2 topsort_dfs.py 1.3 KB
  2.2 two_colorability.py 2.5 KB
  2.3 GraphAdjMat.java 5.2 KB
  2.3 ToOutTree.java 2.4 KB
  2.3 TopsortDfs.java 2.2 KB
  2.3 TwoColorability.java 3.3 KB
  2.3 dijkstra.py 2 KB
  2.3 hierholzer.py 1.7 KB
  2.3 prim.pptx 3.8 MB
  2.4 dijkstra's algorithm.pptx 4.1 MB
  2.4 prim.py 2.1 KB
  2.5 FibonacciHeap.java 23.8 KB
  2.5 Tuple.java 307.2 B
  2.6 Tuple.java 307.2 B
  3. Adjacency list vs adjacency matrix.mp4 71.6 MB
  3. Adjacency list vs adjacency matrix.srt 13.8 KB
  3. BFS-based topological sort algorithm (Kahn's algorithm).mp4 77.1 MB
  3. BFS-based topological sort algorithm (Kahn's algorithm).srt 16.5 KB
  3. Bellman-Ford algorithm.mp4 200.6 MB
  3. Bellman-Ford algorithm.srt 34.4 KB
  3. Checking k-colorability with backtracking.mp4 62 MB
  3. Checking k-colorability with backtracking.srt 14 KB
  3. Kruskal's algorithm.mp4 82.7 MB
  3. Kruskal's algorithm.srt 14 KB
  3. Problem Reconstruct itinerary.html 1.6 KB
  3. Python crash course (optional).html 9 KB
  3. Solution All nodes distance k in a tree problem.mp4 51.1 MB
  3. Solution All nodes distance k in a tree problem.srt 10.4 KB
  3. Solution Path exists in a graph.mp4 49.7 MB
  3. Solution Path exists in a graph.srt 10.5 KB
  3 9.8 KB
  3.1 Disjoint-set data structure YouTube video.html 102.4 B
  3.1 adj list vs adj mat.pptx 1.5 MB
  3.1 bellman ford.pptx 3 MB
  3.1 dfs path exists.pptx 839.5 KB
  3.1 distance_k.py 2.9 KB
  3.1 k colorability.pptx 1 MB
  3.1 topological sort bfs.pptx 1.3 MB
  3.2 DisjointSet.java 1.2 KB
  3.2 DistanceK.java 4.2 KB
  3.2 bellman_ford.py 3.2 KB
  3.2 dfs_path_exists.py 1.1 KB
  3.2 k_colorability.py 2 KB
  3.2 topsort_bfs.py 1.3 KB
  3.3 BellmanFord.java 5.8 KB
  3.3 DfsPathExists.java 1.5 KB
  3.3 KColorability.java 2.6 KB
  3.3 Kruskal.java 3.5 KB
  3.3 TopsortBfs.java 2.2 KB
  3.3 nodes at a distance k.pptx 895.2 KB
  3.4 Edge.java 512 B
  3.4 kruskal.pptx 1.6 MB
  3.5 Tuple.java 307.2 B
  3.5 kruskal.py 2.9 KB
  4. Floyd-Warshall algorithm.mp4 196.9 MB
  4. Floyd-Warshall algorithm.srt 36 KB
  4 83.7 KB
  4. Breadth-first search (BFS) algorithm.mp4 77.5 MB
  4. Breadth-first search (BFS) algorithm.srt 17.2 KB
  4. Greedy coloring.mp4 71.3 MB
  4. Greedy coloring.srt 13 KB
  4. Problem Find all possible recipes.html 1.4 KB
  4. Problem Min cost to connect all points.html 1.3 KB
  4. Quiz Adjacency lists and matrices.html 204.8 B
  4. Quiz What is a tree.html 204.8 B
  4. Solution Reconstruct itinerary.mp4 41.8 MB
  4. Solution Reconstruct itinerary.srt 6.5 KB
  4. Terminology and types of graphs.mp4 146 MB
  4. Terminology and types of graphs.srt 25.3 KB
  4.1 bfs_visualization.py 2.8 KB
  4.1 floyd warshall.pptx 2.2 MB
  4.1 greedy coloring.pptx 1.4 MB
  4.1 types and terms.pptx 2.8 MB
  4.2 Bfs.java 2.1 KB
  4.2 floyd_warshall.py 2.2 KB
  4.2 greedy_coloring.py 1 KB
  4.2 reconstruct_itinerary.py 1.8 KB
  4.3 FloydWarshall.java 3.8 KB
  4.3 GreedyColoring.java 1.8 KB
  4.3 ReconstructItinerary.java 3 KB
  4.3 bfs.py 1.4 KB
  4.4 breadth first search.pptx 1.7 MB
  5. Johnson's algorithm.srt 13.2 KB
  5 311.4 KB
  5. Heuristics (Welsh-Powell, DSatur).mp4 111.7 MB
  5. Heuristics (Welsh-Powell, DSatur).srt 23.9 KB
  5. Johnson's algorithm.mp4 77.8 MB
  5. Problem Minimum edges from start to end.html 1 KB
  5. Solution Find all possible recipes problem.mp4 79.8 MB
  5. Solution Find all possible recipes problem.srt 14.7 KB
  5. Solution Min cost to connect all points problem.mp4 40.2 MB
  5. Solution Min cost to connect all points problem.srt 6.3 KB
  5. What is a Hamiltonian pathcycle.mp4 44.2 MB
  5. What is a Hamiltonian pathcycle.srt 7.6 KB
  5.1 Johnson.java 3.9 KB
  5.1 coloring heuristics.pptx 2.4 MB
  5.1 find recipes.pptx 647.8 KB
  5.1 hamiltonian paths.pptx 966 KB
  5.1 min cost to connect all points.pptx 936.9 KB
  5.2 DSatur.java 2.4 KB
  5.2 find_possible_recipes.py 2 KB
  5.2 johnson.py 2.3 KB
  5.2 min_cost_connect.py 1.5 KB
  5.3 FindPossibleRecipes.java 2.9 KB
  5.3 MinCostConnect.java 1.9 KB
  5.3 dsatur.py 1.3 KB
  5.4 welsh_powell.py 1 KB
  5.5 WelshPowell.java 1.9 KB
  6 290.9 KB
  6. Hamiltonian pathcycle finding algorithms.mp4 46.2 MB
  6. Hamiltonian pathcycle finding algorithms.srt 11.8 KB
  6. Problem Sudoku solver.html 2.3 KB
  6. Quiz Minimum spanning trees.html 204.8 B
  6. Quiz Topological sort.html 204.8 B
  6. Shortest path in unweighted graphs.mp4 46.1 MB
  6. Shortest path in unweighted graphs.srt 8.5 KB
  6. Solution Minimum edges from start to end.mp4 44.4 MB
  6. Solution Minimum edges from start to end.srt 8.9 KB
  6.1 hamiltonian backtracking.pptx 948.8 KB
  6.1 shortest path with unweighted graphs.pptx 901.3 KB
  6.2 bfs_min_edges.py 1 KB
  6.2 hamiltonian_backtracking.py 1.2 KB
  6.2 shortest_path_unweighted.py 1.7 KB
  6.3 BfsMinEdges.java 1.4 KB
  6.3 HamiltonianBacktracking.java 1.8 KB
  6.3 ShortestPathUnweighted.java 3.5 KB
  7. DFS and BFS in implicit graphs.mp4 56.6 MB
  7. DFS and BFS in implicit graphs.srt 11.7 KB
  7. Shortest path in directed acyclic graphs.mp4 86.4 MB
  7. Shortest path in directed acyclic graphs.srt 16.5 KB
  7. Solution Let's make a Sudoku solver.mp4 55.7 MB
  7. Solution Let's make a Sudoku solver.srt 13.8 KB
  7.1 bfs_grid.py 1.4 KB
  7.1 dag shortest path.pptx 1.7 MB
  7.1 sudoku coloring.pptx 2.5 MB
  7.2 BfsGrid.java 1.8 KB
  7.2 shortest_path_dag.py 4.2 KB
  7.2 sudoku_solver.py 2 KB
  7.3 ShortestPathDAG.java 6.5 KB
  7.3 SudokuSolver.java 3.2 KB
  7.3 dfs and bfs in hidden.pptx 1.7 MB
  7.4 dfs_grid.py 1.4 KB
  7.5 DfsGrid.java 1.6 KB
  7.6 Flood fill algorithm YouTube video.html 102.4 B
  8. Quiz Graph coloring.html 204.8 B
  TutsNode.net.txt 102.4 B
  [TGx]Downloaded from torrentgalaxy.to .txt 614.4 B
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  ▲ 271 total files

Description


Description

This Graph theory algorithms will teach students the fundamental concepts and algorithms of graph theory with real life examples and eye-appealing visualizations. The course will cover topics such as graph representation, graph traversal, topological sort, shortest paths, minimum spanning trees, graph coloring… With a total of more than 20 covered algorithms.

Discussed algorithms will be implemented in detail by using a programming language to give a better understanding for students. Captions, practice problems, quizzes, slides, and source code will also be here to make the learning experience way better.

By the end of the course, students will have a strong understanding of graph algorithms and be able to apply their knowledge to solve problems in computer science, mathematics, and beyond.

This course is ideal for students who are looking to pursue careers in computer science, mathematics, or related fields, as well as for professionals who want to expand their knowledge of graph theory algorithms.

Covered algorithms:

Graph traversal:
Depth-first search
Breadth-first search
Topological sorting:
Depth-first search based topological sort
Breadth-first search based topological sort (Kahn’s algorithm)
Shortest path:
Dijkstra’s algorithm
Bellman-Ford algorithm
Floyd-Warshall algorithm
Johnson’s algorithm
Shortest path for unweighted graphs algorithm
Shortest path for directed acyclic graphs (1st approach) algorithm
Shortest path for directed acyclic graphs (2nd approach) algorithm
Trees and minimum spanning trees:
Spanning tree algorithm
Graph to out-tree algorithm
Prim’s algorithm
Kruskal’s algorithm
Eulerian/Hamiltonian paths and cycles:
Hierholzer’s algorithm
Hamiltonian cycle backtracking algorithm
Graph coloring:
2-colorability algorithm
k-colorability backtracking algorithm
Greedy coloring algorithm
Welsh-Powell heuristic
DSatur heuristic

Who this course is for:

Computer science students
Data science beginners
Software development beginners

Requirements

Basic programming knowledge
Algorithmic techniques knowledge is preferred (recursion, backtracking, dynamic programming…)
Data structures knowledge is preferred (hash table, queue, stack, set, heap…)

Last Updated 2/2023

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