> For the complete documentation index, see [llms.txt](https://docs.bdb.ai/data-science-lab-4/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.bdb.ai/data-science-lab-4/repo-sync-project/tabs-for-a-data-science-lab-project/tabs-for-tensorflow-and-pytorch-environment/notebook/notebook-page/operations-for-an-.ipynb-file.md).

# Operations for an .ipynb File

This section aims at describing the various operations for a Data Science Notebook available under the TensorFlow or PyTorch environment.

A Data Science Notebook created under the PyTorch or TensorFlow environment will contain the following operations:

* **​Datasets:** Add datasets and get a list of all the added datasets.
* **​Secrets**: You can generate Environment Variables to save your confidential information from getting exposed.
* **​Algorithms**: You can get steps on how to do Algorithm Settings and Project-level access to use Algorithms inside Notebook.
* **​Transforms**: Save and load models with transform script, register them, or publish them as an API through the DS Lab module.
* **​Models:** You can train, save, and load the models (Sklearn, Keras/TensorFlow, PyTorch). You can also register a model using this tab.
* **Files:** Create/ Upload data folders or files into the dedicated Data Sandbox location.
* **​Variable Explorer:** Get detailed information on Variables declared inside a Notebook.
* **Writers:** Write the output of the DSL experiments into the supported range of the database writers.
* **​Find and Replace**: You can search for a specific text inside your code and replace it if needed.

{% hint style="info" %}
*<mark style="color:green;">Please Note:</mark> Refer to the* [***Data Science Lab Quick Start Flow***](https://docs.bdb.ai/data-science-lab-4/data-science-lab-quick-start-flow) *page to get an overview of the **Data Science Lab** module in a nutshell.*&#x20;
{% endhint %}