Learn and Use SNA in advance Machine learning

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)

1 How to use SNA for Data Analytics (theory)

Awareness of Python

Awareness of Machine Learning using Python

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.

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)

1 How to use SNA for Data Analytics (theory)

Anyone who want to Learn and Apply SNA using Python

Anyone who want to Learn advance Machine Learning



DOWNLOAD
uploadgig


rapidgator


nitroflare