◆ Kaggle: Your Machine Learning and Data Science Community
Kaggle is the world’s largest data science community with powerful tools and resources to help you achieve your data science goals.
Kaggle, a subsidiary of Google LLC, is an online community of data scientists and machine learning practitioners. Kaggle allows users to find and publish data sets, explore, and build models in a web-based data-science environment, work with other data scientists and machine learning engineers, and enter competitions to solve data science challenges.
◆ UCI Machine Learning Repository
https://archive.ics.uci.edu/ml/index.php
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.
◆ ICSA: The International Chinese Statistical Association
The International Chinese Statistical Association (ICSA) is a non-profit organization. The Association is organized and operated for educational, charitable, and scientific purposes only.
Its objectives are: (1) to promote the theory and applications of statistical disciplines through scholarly activities, including publication of journals in statistics and probability, scientific meetings, and other educational programs; (2) to broaden applications of statistical techniques in all areas of society, including industry and government; (3) to promote better understanding and interest by the general public in statistical methodology and related applications; (4) to promote better communication through the development of standards and common terminology; (5) to foster cooperative efforts among educational, research, industrial, and governmental personnel in statistical activities.
The objectives are pursued without regard to race, creed, color, sex or nationality.
The Association was officially founded at the 1987 Joint Statistical Meetings in San Francisco, CA. The ICSA was incorporated in Delaware on August 8, 1988, then registered with the US IRS as a non-profit organization. Its membership is open to all individuals and organizations in all statistics-related areas..
The Association currently has over 1000 active members, and became a special JSM (Joint Statistical Meeting) partnership in 2008. The ICSA publishes two scientific journals: Statistica Sinica and Statistics in Biosciences. It communicates via its ICSA Bulletin and the ICSA Newsletter.
◆ JSM: Joint Statistical Meetings
https://ww2.amstat.org/meetings/jsm/2022/
JSM Is ... One of the Largest Statistical Events in the World
More than 6,500 attendees from 52 countries
600+ sessions, including invited, topic-contributed, contributed, and poster
More than 1,000 student attendees
75+ employers hiring for more than 200 positions
80+ exhibitors
13 participating societies
It is also one of the broadest, with topics ranging from statistical applications to methodology and theory to the expanding boundaries of statistics, such as analytics and data science.
JSM also offers a unique opportunity for statisticians in academia, industry, and government to exchange ideas and explore opportunities for collaboration. Beginning statisticians (including current students) can learn from and interact with senior members of the profession.
◆ IMS: Institute of Mathematical Statistics
The Institute of Mathematical Statistics is an international professional and scholarly society devoted to the development, dissemination, and application of statistics and probability. The Institute currently has about 4,000 members in all parts of the world. Beginning in 2005, the institute started offering joint membership with the Bernoulli Society for Mathematical Statistics and Probability as well as with the International Statistical Institute. The Institute was founded in 1935 with Harry C. Carver and Henry L. Rietz as its two most important supporters. The institute publishes a variety of journals, and holds several international conference every year.
◆ NeurIPS: Neural Information Processing Systems
https://nips.cc/
The conference was founded in 1987 and is now a multi-track interdisciplinary annual meeting that includes invited talks, demonstrations, symposia, and oral and poster presentations of refereed papers. Along with the conference is a professional exposition focusing on machine learning in practice, a series of tutorials, and topical workshops that provide a less formal setting for the exchange of ideas.
The purpose of the Neural Information Processing Systems annual meeting is to foster the exchange of research on neural information processing systems in their biological, technological, mathematical, and theoretical aspects. The core focus is peer-reviewed novel research which is presented and discussed in the general session, along with invited talks by leaders in their field. On Sunday is an Expo, where our top industry sponsors give talks, panels, demos, and workshops on topics that are of academic interest.
◆ ICML: The International Conference on Machine Learning
https://icml.cc/
The International Conference on Machine Learning (ICML) is the leading international academic conference in machine learning. Along with NeurIPS and ICLR, it is one of the three primary conferences of high impact in machine learning and artificial intelligence research. It is supported by the International Machine Learning Society (IMLS). Precise dates vary from year to year, but paper submissions are generally due at the end of January, and the conference is generally held during the following July. The first ICML was held 1980 in Pittsburgh.
◆ ICLR: The International Conference on Learning Representations (ICLR)
https://iclr.cc/
The International Conference on Learning Representations (ICLR) is a machine learning conference held every spring. The conference includes invited talks as well as oral and poster presentations of refereed papers. Since its inception in 2013, ICLR has employed an open peer review process to referee paper submissions (based on models proposed by Yann LeCun). In 2019, there were 1591 paper submissions, of which 500 accepted with poster presentations (31%) and 24 with oral presentations (1.5%). In 2021, there were 2997 paper submissions, of which 860 were accepted (29%). Along with ICML and NeurIPS, ICLR is one of the three major machine learning and artificial intelligence conferences, and has the highest impact of the three.
