# Dataset Visualization

## How to visualize machine learning datasets

[Deep Lake](https://app.activeloop.ai/) has a web interface for visualizing, versioning, querying, and operating on [machine learning datasets](broken://pages/l4BTTqblFqBjQGs72f0w). It utilizes the Deep Lake format under-the-hood, and it can be connected to datasets stored in all Deep Lake [storage locations](/3.1.0/storage-and-credentials/storage-options.md).

![](/files/Vlwib3N4k6Lg8FuuuQML)

### Visualization can be performed in 3 ways:

1. **In the** [**Deep Lake UI**](https://app.activeloop.ai/) **(most feature-rich and performant option)**
2. **In the** [**python API**](/3.1.0/getting-started/visualizing-datasets.md) **using `ds.visualize()`**
3. **In your own application using** [**our integration options**](/3.1.0/how-it-works/visualizer-integration.md)**.**

### Requirements for correctly visualizing your own datasets

Deep Lake makes assumptions about underlying data types and relationships between tensors in order to display the data correctly. Understanding the following concepts is necessary in order to effectively use the visualizer: 

1. [Data Types (htypes)](https://docs.deeplake.ai/en/latest/Htypes.html)
2. [Relationships between tensors](/3.1.0/how-it-works/tensor-relationships.md)

### Visualizer Controls and Modes

{% embed url="<https://youtu.be/N-yvvo2_rrA>" %}


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