Social Network Analysis(SNA) and Graph Analysis using Python
Learn and Use SNA in advance Machine learning
Ratings 2.63 / 5.00
What You Will 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)
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 Should Attend!
- Anyone who want to Learn and Apply SNA using Python
- Anyone who want to Learn advance Machine Learning
