> For the complete documentation index, see [llms.txt](https://docs.myherb.co.il/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.myherb.co.il/sustainability-journey-star/datasets/publicly-available-datasets-sources.md).

# Publicly Available Datasets Sources

## Popular Dataset Repositories:

1. **Google Dataset Search:** A search engine to find datasets across the web.
2. **Kaggle:** A platform for data science competitions with a vast collection of datasets.
3. **UCI Machine Learning Repository:** A collection of datasets for machine learning research.
4. **AWS Public Datasets:** A repository of datasets hosted on Amazon Web Services.

## **Datasets for Specific Domains:**

* **Computer Vision:** ImageNet, CIFAR-10, MNIST
* **Natural Language Processing:** Wikipedia, Common Crawl, Gutenberg Corpus
* **Healthcare:** MIMIC-III, PhysioNet
* **Finance:** Yahoo Finance, Quandl

## **Other Resources:**

* **Papers With Code:** A website that links research papers with their corresponding code and datasets.
* **Awesome Public Datasets:** A curated list of datasets on GitHub.

## **Accessing Datasets in Colab:**

You can access these datasets in Colab using various methods such as:

1. **Downloading:** Download the dataset directly from the source and upload it to your Colab environment.
2. **Mounting Google Drive:** Mount your Google Drive to Colab and access datasets stored there.
3. **Using APIs:** Many platforms provide APIs to access their datasets directly within Colab.
4. **Using Libraries:** Some libraries, like TensorFlow Datasets, provide pre-built functions to load popular datasets.