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InfoQ Homepage News Machine Learning and Artificial Intelligence - Two Conferences to Attend in 2018

Machine Learning and Artificial Intelligence - Two Conferences to Attend in 2018


The IEEE publishes an annual list of the Top 10 Technology Trends for each upcoming year. Making the list for 2018 are multiple topics surrounding artificial intelligence and machine learning. Deep learning comes in as the IEEE hottest trend for 2018.

Neural networks extract features through a concept of layers. By combining the output from these multiple layers, deeper layers are able to construct more advanced insight from data. This is the central concept around deep learning. Last year’s deep learning approaches have shattered existing baselines in a variety of areas, including image processing, text analysis, and even voice recognition. InfoQ has recently explored aspects and thoughts from industry leaders on deep learning topics with Srini Penchikala’s post on Building GPU Accelerated Workflows with TensorFlow and Kubernetes, Michael Stiefel’s Panel on the Future of AI, and Dylan Raithel’s How Apple Does Realtime Recognition of Handwritten Chinese Characters.

For more in-depth exploration on deep learning and the trends around AI and ML, two upcoming software conferences hosted by InfoQ feature deep learning, innovative advances such as self driving car architecture, and feature extraction for machine learning models. QCon London (March 5-7th) returns for its 12th year to the Westminster area and (April 10-11), the inaugural AI/ML software conference for software engineers (SWEs), begins its run in the San Francisco Bay Area. Both conferences feature individually selected talks from prominent engineers in fields geared towards learning, advancing, and enhancing data centric skill sets for SWEs.

While QCon London has a broader reach than (London features 18 multidisciplinary tracks across a multitude of topics), the conference features a full AI track hosted by Eric Horesnyi (CEO @streamdataio) called The Practice & Frontiers of AI. Talks in the AI track plan to draw heavily from Horesnyi’s connections applying machine learning to the financial trading space. Additionally, presentations touching on deep learning across the entire schedule of over 100 talks include:, the second of the two conferences, is the first annual machine learning and artificial intelligence conference produced by InfoQ. has the tagline Applied AI for Developers. Designed as a conference for SWEs who know they need to apply machine learning and AI in their day-to-day roles to be more effective, is the conference to better learn these use cases for application development. The conference features speakers from companies like Stitch Fix, Google, ebay, Uber, Stripe, and more.

While smaller than QCon London, features a complete conference dedicated to machine learning, artificial intelligence, and data engineering. This includes talks (shorter breadth focused talks and longer case study oriented ones) with mature ML shops, panel discussions with innovators, keynotes from thought leaders, and AMAs with recognized engineers in the space as part of the planned schedule. will feature eight tracks, including an entire track devoted to Deep Learning Application & Practices. The deep learning track is hosted by Supranamaya Ranjan (Director of Engineer @Coinbase) and will focus on applied lessons leveraging the techniques IEEE highlighted as the hottest trend for 2018. Additionally, Brad Klingenberg (VP Data Science @StitchFix) leads two half tracks on sequential data and ML applied to operations. At, you’ll find talks like Holden Karau of Google leading End-to-End ML without a Data Scientist, Mikhail Kourjanski (Lead Data Architect @Paypal) / Gurinder Grewal (Risk Chief Architect @PayPal) discussing Data Pipelines for Real-Time Fraud Prevention at Scale, and Anthony Navarro (Product Lead Robotics and Self Driving Car @Udacity) / Jendrik Joerdening (Data Scientist @Akka Germany) sharing details on how they built a self-driving racing vehicle in a short period of time.

One distinguishing feature of is codelabs. Codelabs, in addition to the normal talks / panels / AMAs you find at a QCon, offer attendees the opportunity to work hands-on with AI tooling followed by the opportunity to get your questions answered, unblock on a tricky part of the code, or simply chat about your own use case with the lab’s creators.

Andrew Ng (former Baidu Chief Scientist, Coursera co-founder, and Stanford Adjunct Professor) in his popular Courseria course Neural Networks and Deep Learning (the latest edition of which started January 15th) referred to machine learning as the new electricity. Ng has previously described how a century ago electricity replaced steam powered machines and transformed transportation, manufacturing, agriculture, and healthcare. Electricity transformed our society into the modern society we know today. Ng believes Artificial Intelligence is poised to be equally transformative today.

Machine learning is one of the trends that needs your attention. We’ve all heard about deep learning and the cool stuff Google is doing with it, but I think that enterprise application product owners will be asking for more of these features. While it’s not trivial to get into, I think machine learning is really a skill set that software engineers should acquire now.
Sander Mak, Sr Software Engineer at Luminis Technology, author of Modular Java Development in Action, Speaker at QCon London 2018

QCon London and are two 2018 software conferences featuring topics central to the AI and ML transformation. AI and ML Topics like deep learning are becoming essential for SWEs to add to their skill sets. These are two examples of ways to start or enhance an SWE’s AI journey.

Registration for QCon London and are both open. For QCon London, register before January 27th and the cost is £1,569 (or £300 off the full ticket price). Tickets for the inaugural cost $1,695 before February 17th (or $100 off the full ticket price). Please email or for additional details.

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