Introduction to Session
In the previous section ,you took a look at knowledge graphs-specifically,WordNet. Inknowledge graphs, nods represent entities and edgesrepresent the relationships between these entities.
Distributional semantics captures the meaning of words. Distributional semantics is divided into three sessions as this is an extensive topic.
We have studied neural networks in the previous module, let us see how we will apply the concepts studied there in distributional semantics
This session will cover the following topics:
- Importance of distributional semantics
- A brief intution of geometric representation of words
- Shortcomings of frequency-based approaches of word vectors such as Bag of Words
Guiedlines for in -module questions
The in-video and in-content questions for this module are not graded. Note that graded questions are given in a separate segment labelled ‘Graded Questions’ at the end of each session. The graded questions will adhere to the following guidelines.
| Firest Attempt Marks | Second Attempt Marks | |
| Question with 2 Attempts | 10 | 5 |
| Question with 1 Attempt | 10 | 0 |