The Top AI & Machine Learning Conferences

In this piece, we’ll look at some of the AI and machine learning conferences that took place in 2018 and highlight some of the best speakers and presentations.

These events form a fundamental part of the machine learning and AI communities because they bring people together to learn from each other as well as forge meaningful collaborations.

We’ll also mention the possible dates for some these conferences so you can look out for them in the coming year.

O’Reilly AI Conference

This conference looks at the latest developments in the AI scene. Some of the topics discussed in this conference include domain-specific architectures, addressing risks in AI such as privacy, security, and ethics. The conference also included a startup showcase, which was won by Clobotics. It also had expos, keynotes, hands-on-training, and social events.

The AI Summit

The aim of this summit that is organized by AI Business is to explore what AI practically means to enterprises. The conference is organized by partnering with IBM Watson, Microsoft, Amazon, Google, Facebook, PwC and Intel among many others. The summit included case study presentations from sectors such as retail, oil & gas, finance & banking, energy, medical, telco & media, transport, and tourism.

AI World

This conference focuses on the application of artificial intelligence for the enterprise. It’s designed for business and technology executives who are keen to learn about the application of enterprise-level AI solutions. Some of the topics covered in the 2018 conference include implementing enterprise AI, AI in health, emerging technologies, and deep learning. You can register for the 2019 conference by following this link.

PyTorch DeveloperConference

This conference covered research and production capabilities in the latest release of PyTorch 1.0. The conference covered topics such as using PyTorch 1.0 from research to production, what’s new in PyTorch 1.0, distributed training, and cloud tooling. The keynote for this conference can be watched here.

PyData Conferences

PyData began in 2012 as a workshop at the Googleplex in Mountain View, California. Since then, the event gained a lot of traction, with conferences being held in multiple cities and Meetups popping up worldwide. It’s an educational program by NumFOCUS, which is a US non-profit organization dedicated to supporting open code development and research. You can follow up on what happened during this year’s event via this Youtube channel.

The upcoming events in 2019 are PyData Miami and PyData London. They have an interesting line up of speakers, such as Wes McKinney, the creator of Pandas. You can get involved by either attending the events, starting your own Meetup, organizing a PyData event, or hosting a PyData Track Conference.

Data Science GO

Data Science GO is organized by Super Data Science, which is run by Kirill Eremenko. Kirill has more six hundred thousand students on Udemy enrolled in forty-seven courses. Some of the topics covered in the Data Science GO 2018 conference include data storytelling, building the future of e-commerce through data science, and the convergence of AI and Blockchain, just to mention a few. You can grab your ticket for the 2019 conference by following this link.

Strata Data Conference

This conference by O’Reilly and Cloudera covers AI & machine learning and implementing business intelligence and analytics. The conference brings together CEOs, CTOs, and data scientists, among many other professionals. This conference also happens in various cities.

The conference covers topics such as deploying machine learning models, data transparency in data products and demonstrating ROI for data products. You can follow O’Reilly on YouTube to catch a glimpse of what transpired during these conferences. Details about 2019 conferences can be found here.

Big Data & Machine Learning Leaders Summit

This summit brings together technology leaders, innovators, and data strategists. The agenda for this event looked like this:

  1. Data-driven Business Management
  2. Data Analytics and Commercial Success
  3. Data Science and Machine Learning
  4. Data Engineering and Architecture
  5. Rewriting Life — Health Data Science
  6. Panel Discussion — Data and AI Technology for Financial Industry
  7. Panel Discussion — Advanced Analytics Wrap-up

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Our team has been at the forefront of Artificial Intelligence and Machine Learning research for more than 15 years and we're using our collective intelligence to help others learn, understand and grow using these new technologies in ethical and sustainable ways.

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