25 Public Datasets for Machine Learning

Datasets are a critical part of machine learning. Any company of sufficient size will have unique domain-specific data in which they can create private datasets. The right data is helpful in building effective AI models that can improve efficiencies and productivity, reduce operational cost, enhance customer service, and ultimately create a competitive advantage. However, preparing the ideal datasets can be a time-consuming process. That’s were public datasets come in handy.

The AI strategy shouldn’t stall while the perfect datasets are being prepared. Public datasets provide organizations with data that can be used to build and test AI models. There are thousands of public datasets available for use, in areas like weather, disease, Twitter, animals, facial recognition, aerial, self-driving, object detection, banking, stock market, and much more. Some of the well-known datasets like ImageNet and MNST are great for using in POC’s to test frameworks, algorithms, libraries, hardware (DIY), and more.

In the matrix below, the first six columns are collections of datasets. For example, Google host more than 100 datasets, some are public, as developed by various government entities and others were created by Google. The same applies to AWS, Microsoft, Kaggle, and so on. The global AI community is coming together and publishing datasets regularly, in the hopes that companies will not only use it to further their business model, but tackle problems like heart disease, diabetes, droughts, poverty, etc. At the same time, some datasets might create concerns, as in those in the area of facial recognition. Below are twenty-five sources of publicly available datasets.