> ## Documentation Index
> Fetch the complete documentation index at: https://docs.encord.com/llms.txt
> Use this file to discover all available pages before exploring further.
# Embedding Plots
The embedding plot is a 2D visualization of your high-dimensional data, where proximity between points indicates similarity. This makes it easy to spot clusters, outliers, and patterns at a glance.
You can draw a rectangular selection on the plot to isolate and explore a specific subset of data points. Use the *Order by* drop-down to switch the visualization between data and label embeddings.
## Calculate Metrics and Embeddings
1. Navigate to **Projects**.
2. Open the **Explore** tab.
3. Click **Metrics & Embeddings**.
4. Click **Compute** for either option.
5. Specify the following:
* **Similarity & Natural language search and quality metrics:** Enable to compute embeddings and quality metrics. Access quality metrics for filtering and sorting.
* **Select embeddings:** Default embeddings are computed by Encord. Alternatively, import and select your own custom embeddings.
* **Embeddings plot, Diversity and Uniqueness metrics:** Enable to compute UMAP reduction to generate 2D embeddings plots to visualize your data. Also access diversity and uniqueness metrics for curation.
6. Click **Start computation**.
## Using Embedding Plots
To use embedding plots for label validation, you must [calculate metrics and embeddings](/platform-documentation/Validation/label-validation-basics#compute-metrics-and-embeddings).
1. Navigate to **Projects**
2. Open the **Explore** tab.
3. Click **Frames** or **Labels**.
4. Click the **Embeddings View** icon.
* Use the V + E shortcut to access the Embeddings View.
* In addition to selecting points within a rectangular area, you can use filters (but not sort or natural language or image search) on the data or labels.
**Data Embedding Plot**
**Label Embedding Plot**