Using IA for know more about the page suggested on the Course received this response. So I decided to share this information's with you. Just in case...

Here’s a concise summary of the page’s main points:

- Purpose and Title:

The page is titled "Embedding projector – visualization of high-dimensional data".

It presents an **interactive tool designed for visualizing and exploring high-dimensional data embeddings, such as word vectors. **

- Data Overview:

The interface indicates that :

** there are 5 tensors available, **

** a notable dataset being Word2Vec **

**consisting of 10,000 points. **

** each data point is represented in a 200-dimensional space, **

** and the words serve as labels. **

• Visualization and Editing Options:

Users can interact with the data through features like:

**labeling by word, **

**editing by word, **

**selecting tags. **

There are functions available for:

**loading new data, **

**publishing, **

downloading,

labeling,

**even “sphereizing” the data, ** which likely means transforming or visualizing the data in a spherical format.

• Dimensionality Reduction Methods:

The tool provides multiple options for projecting the data into lower dimensions for better visualization.

Methods include:

**UMAP, **

**t-SNE, **

PCA (which is noted to be approximate with 5% of the total variance explained),

a** custom option**, along with controls to choose the:

[ ** X, ** **Y, ** ** Z ** components for visualization. ]

• Interactive Features:

Users have control over the data display through features like:

showing all data points,

**isolating selections, **

**clearing selections, **

performing word-based searches.

**Bookmarks are also available to save or mark specific points of interest. **

This summary captures the essential aspects of the page, focusing on its purpose as a visualization tool, the data specifics, and the interactive functionalities available.