Social Network Analysis(SNA) and Graph Analysis using Python
- 4.1
-
![]()
![]()
![]()
![]()
Brief Introduction
Learn and Use SNA in advance Machine learningDescription
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)
Requirements
- Requirements
- Awareness of Python
- Awareness of Machine Learning using Python
Knowledge
- 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)
Shiv Onkar Deepak Kumar
4.1 Raiting
Learning Path: Data Science With Apache Spark 2
- 3.6
-
![]()
![]()
![]()
![]()
![]()
Get started with Spark for large-scale distributed data processing and data science Sounds interesting? Let’s see how easy it is! We then develop a real-world Spark application....
Social Network Analysis (SNA)
- 0.0
-
![]()
![]()
![]()
![]()
![]()
Learn how to conduct a social network analysis to better understand how people seek and share information in learning settings. You will learn to:...
Social Network Analysis(SNA) and Graph Analysis using Python
- 4.1
-
![]()
![]()
![]()
![]()
![]()
Learn and Use SNA in advance Machine learning 1. The content (80% hands on and 20% theory) will prepare you to work independently on SNA projects...
Data Manipulation at Scale: Systems and Algorithms
- 4.3
-
![]()
![]()
![]()
![]()
![]()
Data analysis has replaced data acquisition as the bottleneck to evidence-based decision making --- we are drowning in it. At the end of this course, you will be able to:...
