Discover 10 trusted sources of high-quality, free datasets for a variety of projects. This list includes resources such as Kaggle and Data.gov.
They consist of datasets related to things like machine learning, global development.
Using these sites will help strengthen the data-driven work at no cost while providing large datasets that you can extract information from.
In any data-driven project, having access to quality datasets is crucial, ranging from machine learning models to academic research. Luckily, there are many ways to find free datasets on a variety of topics. Here's a list of ten places to find public datasets on the web.
Kaggle, a part of Google, is a high-profile place for data with over 273,000 datasets available. It is designed for and appeals to data scientists and machine learning enthusiasts with datasets in areas such as computer vision, natural language processing (NLP), and time series. Kaggle also includes challenges and community engagement.
The UCI Machine Learning Repository has existed for many years and has datasets from machine learning literature and supports research using many machine learning paradigms. The datasets vary for classification, regression, and clustering, making them suitable for any type of user, from novices to accomplished researchers.
Google Dataset Search is a search engine designed specifically to discover datasets. It searches datasets from many sources, such as governmental, academic, and organizational. It is a one-stop shop for simplifying the process of finding datasets across the web.
Data.gov is the open data platform of the U.S. government, with over 335,000 datasets on topics ranging from agriculture to climate to energy to health. Many of these datasets can be utilized for policy research or statistical analysis.
The World Bank's Open Data initiative offers free and open access to global development data. Users can find datasets on various topics like economic indicators, education, poverty, and the environment, allowing users to conduct research related to international development or economic trends.
Amazon Web Services has various public datasets available to the public that allow for large-scale analysis. These datasets range in fields like genomics, satellite images, and web crawls and can be accessed freely for tasks in high-performance computing or as sources for training AI.
OpenML is an open platform for sharing and organizing datasets, algorithms, and experiments related to machine learning. It facilitates collaboration in machine learning research and offers a home for datasets, as well as tools to analyze them.
FiveThirtyEight uses data to tell stories about culture, politics, and sports. The datasets it releases are the same tables used in the articles it reports on. These datasets are responsibly structured and often accompanied by an outline of their analysis process. FiveThirtyEight is invaluable for projects related to data visualization and data storytelling because of its datasets.
The EU Open Data Portal provides users with datasets from a range of European institutions. The datasets cover themes including economy, employment, environment, and education and are intended to be used in research and innovation across EU member countries.
Harvard Dataverse is an open-source repository for sharing, citing, and archiving research data. Harvard Dataverse contains datasets across multiple disciplines, ensuring that there is sufficient documentation for others to use the data in their own academic work or professional practice.
Having access to datasets that are free and of high quality is important for growth in data science, machine learning, and research projects. The above platforms offer datasets across a range of datasets that cater to a range of domains and levels of expertise.
By using these free platforms, users can not only improve their projects but also contribute to open data movements and the growth of innovation without needing to spend money.