Fortunately, while commercially sensitive data can be hard to come by, there are still a number of useful datasets available publicly. Many of these are often used as benchmark datasets for specific types of machine learning problems. Examples of common data sources include:
- UCI Machine Learning Repository: This is a collection of almost 300 datasets of various types and sizes for tasks, including classification, regression, clustering, and recommender systems. The list is available at http://archive.ics.uci.edu/ml/.
- Amazon AWS public datasets: This is a set of often very large datasets that can be accessed via Amazon S3. These datasets include the Human Genome Project, the Common Crawl web corpus, Wikipedia data, and Google Books Ngrams. Information on these datasets can be found at http://aws.amazon.com/publicdatasets/.
- Kaggle: This is a collection of datasets used in machine...
