Machine Learning

Social Network Analysis(SNA) and Graph Analysis using Python

Learn and Use SNA in advance Machine learning


What you’ll learn:
1. The content (80% hands on and 20% theory) will prepare you to work independently on SNA projects
2. Learn – Basic, Intermediate and Advance concepts
3. Graph’s foundations (20 techniques)
4. Graph’s use cases (6 use cases)
5. Link Analysis (how Google search the best link/page for you)
6. Page Ranks
7. Hyperlink-Induced Topic Search (HITS; also known as hubs and authorities)
8. Node embedding
9. Recommendations using SNA (theory)
10. Management and monitoring of complex networks (theory)
11. How to use SNA for Data Analytics (theory)

Requirements
Awareness of Python
Awareness of Machine Learning using Python

Description
As practitioner of SNA, I am trying to bring many relevant topics under one umbrella in following topics so that it can be uses in advance machine learning areas.

1. The content (80% hands on and 20% theory) will prepare you to work independently on SNA projects

2. Learn – Basic, Intermediate and Advance concepts

3. Graph’s foundations (20 techniques)

4. Graph’s use cases (6 use cases)

5. Link Analysis (how Google search the best link/page for you)

6. Page Ranks

7. Hyperlink-Induced Topic Search (HITS; also known as hubs and authorities)

8. Node embedding

9. Recommendations using SNA (theory)

10. Management and monitoring of complex networks (theory)

11. How to use SNA for Data Analytics (theory)

Who this course is for
Anyone who want to Learn and Apply SNA using Python
Anyone who want to Learn advance Machine Learning

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