Top 5 Public Datasets for Machine Learning by TechFunne

Top 5 Public Datasets for Machine Learning

Top 5 Public Datasets for Machine Learning

Machine learning capabilities continue to grow and help to push businesses forward. Finding public dataset resources can help people continue to research machine learning and find more useful ways of using it in business. Machine learning datasets help to train machine learning programs, ultimately giving them the knowledge and context on which to base their learning and responses.

There are two types of datasets: training and test. Training is essentially the knowledge parameters given to a program to optimize it for functionality in whatever the task it’s being developed for. Test data is used after optimization to make sure that the machine learning program is functioning as projected or desired.

How to find the best public datasets for machine learning projects.

Datasets are crucial to training machine learning functions – here’s where to find the best free, reliable resources.

Getting the right data in the right format can be a chore for some researchers or programmers. There are lots of repositories of open data sets available that can be used in training the neural networks that support machine learning. Here are some of the top public datasets to help with training and optimizing for your machine learning projects.

General Data

  1. DataPortals: This site offers access to data portals all around the globe. It has an easy-to-use search feature that enables users to find their area of interest. Because of the fact that these sets of data can be highly specific (like data on self-driving cars) to very general, it’s important that a resource has easy-to-use navigation to help programmers find the information relevant to them and to their projects.
  1. Knoema: The claim to fame for this machine learning data tool is that it’s said to have the biggest collection of publicly available data on the web, with data that covers 1000 topics from over 1000 sources. This means that programmers can explore datasets by source or topic and also find just about any training data they could be looking for.
  1. gov: The US government is a useful tool for free data. Data.gov is a public data repository that includes over 237,545 sets of data related to anything from weather and climate, produce prices, and other geographical information.
  1. Eurostat: Similarly, there is a source of open data sets related to the EU. These freely available statistics and datasets are related to agriculture, economy, regional statistics, transport, energy, and more.

Specific or Niche Data

There are also a lot of tools that cater to making very specific data available. From photography and images to language processing to information on self-driving cars and other technology, public datasets exist to help support machine learning projects in these fields.

  1. GengoAI: is an AI development platform that focuses on language, communication, and speech projects. They compiled a list of highly specific, readily available public datasets from sources that range from government offices to Reddit boards. According to their research, some of the datasets that are available include topics and information like:
  • Chronic disease data, data on disease indicators across the US
  • Google trends, a searchable database that can list and analyze internet search activity
  • Quandl, a source for economic and financial data
  • Labelme, an image database
  • Stanford Dogs Dataset, which has over 20,000 images of over 120 different dog breeds
  • Amazon reviews, a collection of Amazon product reviews spanning 18 years and including user information, rating, and text review
  • Jeopardy, an archive of over 200,000 questions and answers from the show Jeopardy

Machine learning datasets are key to creating smarter business solutions and more advanced programs. The good news is there’s a massive amount of data available to help train and optimize machine learning tools for their tasks. Finding the right dataset is an important first step, and knowing that there are so many publicly sourced and open options available can be a great start for your business.

Marianne Chrisos
Marianne Chrisos
Born in Salem, Massachusetts, growing up outside of Chicago, Illinois, and currently living near Dallas, Texas, Marianne is a content writer as a company near Dallas and contributing writer around the internet. She earned her master's degree in Writing and Publishing from DePaul University in Chicago and has worked in publishing, advertising, digital marketing, and content strategy.
    Top
    Want to stay up-to-date with news and information from TechFunnel.com?

    Subscribe Now