The current technological landscape has exhibited the need for feeding Machine Learning systems with useful training data sets. Training data helps a program understand how to apply technology such as neural networks. This is to help it to learn and produce sophisticated results.
The accuracy and relevance of these sets pertaining to the ML system they are being fed into are of paramount importance, for that dictates the success of the final model. For example, if a customer service chatbot is to be created which responds courteously to user complaints and queries, its competency will be highly determined by the relevancy of the training data sets given to it.
To facilitate the quest for reliable training data sets, here is a list of resources which are available free of cost.
Owned by Google LLC, Kaggle is a community of data science enthusiasts who can access and contribute to its repository of code and data sets. Its members are allowed to vote and run kernel/scripts on the available datasets. The interface allows users to raise doubts and answer queries from fellow community members. Also, collaborators can be invited for direct feedback.
The training data sets uploaded on Kaggle can be sorted using filters such as usability, new and most voted among others. Users can access more than 20,000 unique data sets on the platform.
Kaggle is also popularly known among the AI and ML communities for its machine learning competitions, Kaggle kernels, public datasets platform, Kaggle learn and jobs board.
Examples of training datasets found here include Satellite Photograph Order and Manufacturing Process Failures.
Registry of Open Data on AWS
As its website displays, Amazon Web Services allows its users to share any volume of data with as many people they’d like to. A subsidiary of Amazon, it allows users to analyze and build services on top of data which has been shared on it. The training data can be accessed by visiting the Registry for Open Data on AWS.
Each training dataset search result is accompanied by a list of examples wherein the data could be used, thus deepening the user’s understanding of the set’s capabilities.
The platform emphasizes the fact that sharing data in the cloud platform allows the community to spend more time analyzing data rather than searching for it.
Examples of training datasets found here include Landsat Images and Common Crawl Corpus.
UCI Machine Learning Repository
Run by the School of Information & Computer Science, UC Irvine, this repository contains a vast collection of ML system needs such as databases, domain theories, and data generators. Based on the type of machine learning problem, the datasets have been classified. The repository has also been observed to have some ready to use data sets which have already been cleaned.
While searching for suitable training data sets, the user can browse through titles such as default task, attribute type, and area among others. These titles allow the user to explore a variety of options regarding the type of training data sets which would suit their ML models best.
The UCI Machine Learning Repository allows users to go through the catalog in the repository along with datasets outside it.
Examples of training data sets found here include Email Spam and Wine Classification.
Microsoft Research Open Data
The purpose of this platform is to promote the collaboration of data scientists all over the world. A collaboration between multiple teams at Microsoft, it provides an opportunity for exchanging training data sets and a culture of collaboration and research.
The interface allows users to select datasets under categories such as Computer Science, Biology, Social Science, Information Science, etc. The available file types are also mentioned along with details of their licensing.
Datasets spanning from Microsoft Research to advance state of the art research under domain-specific sciences can be accessed in this platform.
GitHub is a community of software developers who apart from many things can access free datasets. Companies like Buzzfeed are also known to have uploaded data sets on federal surveillance planes, zika virus, etc. Being an open-source platform, it allows users to contribute and learn about training data sets and the ones most suitable for their AI/ML models.
Socrata Open Data
This portal contains a vast variety of data sets which can be viewed on its platform and downloaded. Users will have to sort through data which is currently valid and clean to find the most useful ones. The platform allows the data to be viewed in a tabular form. This added with its built-in visualization tools makes the training data in the platform easy to retrieve and study.
Examples of sets found in this platform include White House Staff Salaries and Workplace Fatalities by US State.
This subreddit is dedicated to sharing training datasets which could be of interest to multiple community members. Since these are uploaded by everyday users, the quality and consistency of the training sets could vary, but the useful ones can be easily filtered out.
Examples of training datasets found in this subreddit include New York City Property Tax Data and Jeopardy Questions.
This is basically a data aggregator in which training data from scientific papers can be accessed. The training data sets found here are in many cases massive and they can be accessed directly on the site. If the user has a BitTorrent client, they can download any available training data set immediately.
Examples of available training data sets include Enron Emails and Student Learning Factors.
In an age where data is arguably the world’s most valuable resource, the number of platforms which provide this is also vast. Each platform caters to its own niche within the field while also displaying commonly sought after datasets. While the quality of training data sets could vary across the board, with the appropriate filters, users can access and download the data sets which suit their machine learning models best. If you need a custom dataset, do check us out here, share your requirements with us, and we’ll more than happy to help you out!data, dataset, dataset resources, free resources, machine learning, ML, ml data, ml models, ml systems, ml training data, training data, training dataset, training set