Category: Computer Science

School of Data is a global network committed to advancing data literacy in civil society. Information that directly impact people’s lives is increasingly accessible but civil society is falling behind in making effective use of it. Through our global network of data literacy practitioners and trainers, School of Data seeks to address this data skills gaps in order to amplify the messages of civil society through the use of data. We level the playing field by ensuring that civil society organisations and newsrooms have the knowledge, resources and tools they need to participate fully in the information age.

https://schoolofdata.org/

Level: All

CiteSeerx is an evolving scientific literature digital library and search engine that has focused primarily on the literature in computer and information science. CiteSeerx aims to improve the dissemination of scientific literature and to provide improvements in functionality, usability, availability, cost, comprehensiveness, efficiency, and timeliness in the access of scientific and scholarly knowledge.

Rather than creating just another digital library, CiteSeerx attempts to provide resources such as algorithms, data, metadata, services, techniques, and software that can be used to promote other digital libraries.

https://csxstatic.ist.psu.edu/home

Level: All

AITopics is the Internet’s largest collection of information about the research, the people, and the applications of Artificial Intelligence. Our mission is to educate and inspire through a wide variety of curated and organized resources gathered from across the web. AITopics is brought to you by The Association for the Advancement of Artificial Intelligence (AAAI).

AITopics is intended primarily for instructors of AI courses and students from high school through first-year graduate school.

https://aitopics.org/misc/about

Level: All

The Insight Centre for Data Analytics is one of Europe’s largest data analytics research organisations, with 400+ researchers, more than 80 industry partners and over €100 million of funding.

Insight is funded by Science Foundation Ireland, and is made up of four main centres: Insight@DCU, Insight@NUI Galway, Insight@UCC and Insight@UCD as well as a number of affiliated bodies.

Each of Insight’s main centres has a long track record of data analytics research. In July 2013 they came together under Science Foundation Ireland as Insight. The size of the centre allows for collaboration on a large scale, which enables the organisation to compete for funding and opportunities at a much higher level.

https://www.insight-centre.org/

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The ADAPT Centre, funded by Science Foundation Ireland focuses on developing next generation digital technologies that transform how people communicate by helping to analyse, personalise and deliver digital data more effectively for businesses and individuals.

ADAPT researchers are based in four leading universities: Trinity College Dublin, Dublin City University, University College Dublin and Dublin Institute of Technology. ADAPT’s transformative tools allow you explore video, text,speech and image data in a natural way across languages and devices, helping companies unlock opportunities that exist within digital content to re-imagine how to connect people, process and data to realise new economic value.

https://www.adaptcentre.ie/research

Level: All

Open Machine Learning : Ideas and results from the open machine learning community

Level: All

https://www.openml.org/

Inside Kaggle you’ll find all the code & data you need to do your data science work. Use over 19,000 public datasets and 200,000 public notebooks to conquer any analysis in no time.

https://www.kaggle.com/

Level: All

The UCI Machine Learning Repository is a collection of databases, domain theories, and data generators that are used by the machine learning community for the empirical analysis of machine learning algorithms. The archive was created as an ftp archive in 1987 by David Aha and fellow graduate students at UC Irvine. Since that time, it has been widely used by students, educators, and researchers all over the world as a primary source of machine learning data sets.

As an indication of the impact of the archive, it has been cited over 1000 times, making it one of the top 100 most cited “papers” in all of computer science. The current version of the web site was designed in 2007 by Arthur Asuncion and David Newman, and this project is in collaboration with Rexa.info at the University of Massachusetts Amherst. Funding support from the National Science Foundation is gratefully acknowledged.

https://archive.ics.uci.edu/ml

Level: All