Learn Graphs and Social Network Analytics Using Python

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Learn Graphs and Social Network Analytics Using Python (Size: 912.73 MB)
  01 Introduction
  001 Course Intro.mp4 14.24 MB
  02 Overview of networkX
  001 Overview of networkX.mp4 35.98 MB
  002 NetworkX Basics.mp4 20.54 MB
  03 Installation of networkX and iPython Notebooks
  001 Installation of networkX and iPython Notebooks.mp4 39.4 MB
  04 Creating nodes using networkX
  001 Creating Nodes using networkX.mp4 9.8 MB
  05 Adding edges to graphs
  001 Adding edges to graphs.mp4 11.43 MB
  06 Getting graph properties
  001 Getting graph properties.mp4 20.31 MB
  07 Node Manipulation
  001 Node manipulation.mp4 5.52 MB
  08 Adding attributes to graphs
  001 Adding attributes to graphs-01.mp4 10.75 MB
  002 Adding attributes to graphs-02.mp4 14.11 MB
  09 Adding edge attributes to graphs
  001 Adding edge attributes to graphs-01.mp4 15.02 MB
  002 Adding edge attributes to graphs-02.mp4 11.8 MB
  10 Creating DiGraphs
  001 Creating DiGraphs-01.mp4 21.52 MB
  002 Creating DiGraphs-02.mp4 12.78 MB
  11 Creating MultiGraphs
  001 Creating MultiGraphs.mp4 19.02 MB
  12 Creating MultiDiGraphs
  001 Creating MultiDiGraphs.mp4 19.1 MB
  13 Graph Generators
  001 Graph generators-01.mp4 18.14 MB
  002 Graph generators-02.mp4 18.2 MB
  14 Graph Metrics
  001 Shortest Path.mp4 16.75 MB
  002 Clustering Coefficient.mp4 12.43 MB
  15 Defining Functions
  001 Define functions to draw graphs-01.mp4 7.65 MB
  002 Define functions to draw graphs-02.mp4 9.12 MB
  003 Create nodes using a custom function.mp4 10.62 MB
  004 Delete nodes using a custom function.mp4 9.95 MB
  005 Delete edges using a custom function.mp4 10.57 MB
  006 Custom node size and node color using a custom function.mp4 11.64 MB
  007 Custom edge colors using a custom function.mp4 12.25 MB
  16 Graph Visualizations
  001 Draw Images using networkX.mp4 12.61 MB
  002 Draw circular graphs.mp4 15.23 MB
  003 Draw bar graph using betweenness centrality.mp4 9.24 MB
  17 Nodes , Degrees and Centrality Metrics
  001 Nodes, Degrees and Centrality.mp4 9.13 MB
  18 Random Graphs
  001 Grid Graphs.mp4 15.69 MB
  002 Circular Trees.mp4 7.78 MB
  003 Bipartite Graphs.mp4 24.15 MB
  004 Some random graphs.mp4 15.78 MB
  005 House Graph.mp4 16.7 MB
  19 Small Famous Graphs
  001 Small famous graphs.mp4 10.27 MB
  002 Famous social network graphs.mp4 37.29 MB
  003 Classical graphs.mp4 30.97 MB
  20 Reading and writing graph files
  001 Writing files.mp4 12.49 MB
  002 Reading files.mp4 4.75 MB
  003 Writing edgeList graphs.mp4 17.58 MB
  004 Reading graphs files using open function.mp4 7.54 MB
  005 Reading edgeList graphs.mp4 7.63 MB
  21 Social Network Analysis
  001 Social network -00.mp4 25.47 MB
  002 Social network -01.mp4 27.32 MB
  003 Social network -02.mp4 14.62 MB
  004 Social network -03.mp4 12.4 MB
  005 Social network -04.mp4 15.72 MB
  006 Social network -05.mp4 12.75 MB
  007 Social network -06.mp4 24.35 MB
  22 Subgraphs
  001 Subgraphs.mp4 9.73 MB
  002 Triangles.mp4 11.81 MB
  23 Facebook Social Network Analysis
  001 Facebook Social Network Analysis.mp4 26.45 MB
  002 Facebook Social Network Analysis.mp4 56.63 MB
  24 Conclusions
  001 Thank you Good Bye.mp4 2.03 MB
  ▲ 56 total files

Description


What you'll learn
Create graphs using NetworkX package
Create nodes of a graph
Create edges of a graph
Determine the attributes of a node and edges
Analyze social networks likeand Twitter
Students will learn more about properties of a graph
Learn about Clustering coefficient , Betweenness centrality, degree centrality etc
Learn about Connected graphs, Bipartite graphs, etc
Learn about the types of graphs used for social network analysis


Course goals :

-At the end of the course students should be able to learn some basics of graph theory

- Students should be able to analyzesocial networks

- Students should take the simple quizzes

- Students should know what is directed and undirected graphs

- Students should be able to visualize graphs using different graph plots

- You can use this course to analyze the world as a network

- Everything in this world is now connected

- Extract useful information from graphs

Life time access to the course. What are you waiting for? Learn practical graph and social network analytics today that would improve your career and increase your knowledge.

Who this course is for:
Beginners who have never programmed in python before
Students who are Graph Enthusiast
Intermediate python programmers who want to level up their skills
Students who want to analyze social networks likeand Twitter
Mathematics students who wants to apply their knowledge in Graph Theory

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