10 Upcoming AI and Big Data Analytics Conferences to Attend in 2021
AI and big data analytics conferences, summits, and talks are a great way to share and enhance knowledge about the rapidly evolving technologies. Such events allow people and tech enthusiasts to interact with the world’s top leaders and develop their skills in related fields. The COVID-19 pandemic has undoubtedly postponed or cancelled many such conferences and forced organizers to move to virtual. However, as the world is returning to its own place, many events are scheduled to take place in-person.
This article provides a list of 10 upcoming AI and big data analytics conferences to attend in 2021. So, mark your calendar and choose which one to attend or submit to talks to.
SubSurface: The Cloud Data Lake Conference
Date: January 27-28
This virtual conference will explore the latest open source innovations and offers real-world use cases. The conference will provide how to build fast, cost-efficient cloud data lakes, and attendees will get live 1:1 demos from leading technology vendors. Attendees will dive into innovative open source projects such as Apache Iceberg, Amundsen, InfluxDB IOx, and more, and join the community of industry experts and community leaders. Attendees will hear firsthand from technology leaders at companies such as Netflix, USAA, Adobe, Microsoft, and AWS about their experiences architecting and building modern data lakes.
RE.WORK Deep Learning 2.0 Virtual Summit
Date: January 28-29
This virtual summit discusses the latest technology advancements and practices through five categories including the Deep Learning Landscape stage, Reinforcement Learning stage, Generative model stage, Enterprise AI stage, and Ethics & Social responsibility stage. The summit brings together speakers to discuss from renowned companies like Salesforce, SonyAI, UC Berkeley, Google, OpenAI, DeepMind, and more, along with experts from top universities such as Princeton University, Unversity of Buffalo, and more.
AAAI Conference on Artificial Intelligence
Date: February 2-9
This is the 35th AAAI Conference on Artificial Intelligence that will be held virtually on February 2-9, 2021. The purpose of the AAAI conference is to promote research in artificial intelligence and scientific exchange among AI researchers, practitioners, scientists, and engineers in affiliated disciplines. AAAI-2021 will have a diverse technical track, student abstracts, poster sessions, invited speakers, tutorials, workshops, and exhibit and competition programs, all selected according to the highest reviewing standards.
DATAcated Conference 2021
Date: February 9-11
This conference is focused on three key themes: Extracting Business Value from Data; Exploring Trends in AI & Machine Learning; and Data Storytelling – the ‘Last Mile’ of Analytics. The conference will bring together the very best speakers including Ben Taylor, Chief AI Evangelist at DataRobot (Keynote Speaker); Cindi Howson, CDSO at ThoughtSpot (Keynote Speaker); Inna Saboshchuk, Ph.D., Senior Data Product Manager at Levi Strauss & Co.; Kirk Borne, Principal Data Scientist & Data Science Fellow, and Executive Advisor at Booz Allen Hamilton, and others.
WiDS Worldwide Conference
Date: March 8
The Women in Data Science (WiDS) conference is a technical conference featuring extraordinary women doing outstanding work in data science and related fields such as AI in a wide range of domains. This is the first-ever 24-hour virtual conference bringing together thought leaders around the world, from academia and industry to non-profits and government. WiDS Worldwide includes WiDS regional events hosted by WiDS Ambassadors, featuring speakers from their respective regions.
RE.WORK Deep Learning Summit
Date: April 15-16
Location: London, UK and Online
This summit will bridge the gap between the latest technological research advancements and real-world applications in business and society. This brings together the latest technology advancements and practical examples to apply AI to solve business and societal challenges. Attendees will hear from the leaders at DeepMind, Facebook AI Research, Microsoft Research, and more.
World Data Summit
Date: May 19-21
Location: Amsterdam, The Netherlands
This three-day conference will provide a better understanding of developing an analytical model for business and customer growth. Experts will discuss all aspects of data analysis, how to work with unstructured data, how to upgrade data visualization and interpretability to the next level. Attendees will dig deeper into customer analytics and intensify their technical knowledge by choosing a designated workshop day.
The Federated & Distributed Machine Learning Conference
Date: June 18-19
This conference will provide a dynamic learning environment for both academic and industry leaders to facilitate the growth of federated learning and establish the networks that will be vital to its development and promulgation. Presentations will tackle the basics of federated learning, its complexities and the technical challenges, such as model poisoning, which need to be met in order for federated learning to truly meet the goal of successful decentralized AI, which in turn can have a tremendous impact on the future of business and society.
International Conference on Machine Learning and Data Mining (MLDM) 2021
Date: July 18-22
Location: New York, USA
This conference will bring together researchers from all over the world who deal with machine learning and data mining to discuss the recent status of the research and to direct further developments. Basic research papers as well as application papers are welcome. All kinds of applications are welcome but special preference will be given to multimedia-related applications, biomedical applications, and webmining.
World AI Show, Singapore
Date: October 16
This is the one-of-a-kind virtual gathering of pre-qualified CIOs, CEOs, CTOs, Heads of AI, CDOs, Heads of Innovation and International AI & ML experts. Attendees will have access to workshops, use-case presentations, product exhibitions, panel discussions and tech talks to find solutions for issues and trends within the AI space.
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