QCon.ai, the dedicated artificial intelligence and machine learning conference for software engineers, will be returning to San Francisco for its second year in April 2019. Organised by the people behind InfoQ and QCon, the program committee are today announcing the tracks for the 2019 AI and ML conference.
- Predictive Architectures in the Real World: A case study focused look at end-to-end predictive pipelines from places like Salesforce, Uber, LinkedIn & Netflix.
- Deep Learning in Practice: Deep learning lessons using Tensorflow, Keras, PyTorch, and Caffe including use cases on machine translation, computer vision & image recognition.
- Papers to Production: CS in the Real World: Groundbreaking papers making real-world impact in software.
- Solving Software Engineering Problems with Machine Learning: Anomaly detection, Machine learning in IDEs, Bayesian optimization for configuration; these are machine learning techniques for more effective software engineering.
- Groking Timeseries & Sequential Data: Techniques, practices, and approaches, including image recognition, NLP, predictions & modeling.
- AI Meets Physical World: Where AI touches the physical world - think drones, ROS, NVidia, TPU and more.
Each of the QCon.ai tracks are full day, individually curated themes on a topic in machine learning. Designed to be flexible, attendees can stay in an individual track or move between as many sessions as they like throughout the two day conference. In addition, all sessions videos are made available following the conference to attendees at no additional cost (the 2018 videos are now available). Each of these technical sessions are lessons and use cases from leading shops like Google, Airbnb, PayPal and Twitter, and are focused on helping software engineers apply machine learning in their day-to-day work. Prathima Donapudi, Sr Software Engineer @Netflix who attended the 2018 event described it this way: "High quality talks from the innovators in the industry with no sales pitch. Helped me to get a much broader and deeper understanding on where AI is headed and some of the areas where it is actively applied."
Last year's inaugural QCon.ai included talks from Rachel Thomas (fast.ai founder & USF assistant professor on Analyzing & Preventing Unconscious Bias in Machine Learning), Holden Karau (Spark Committer & Open Source Developer Advocate on End to Eng ML with Speak & Beam), Chakri Cherukuri (Quantitative Researcher @Bloomberg on Interactive Visualization Techniques), and Matt Ranney (Sr. Staff Engineer @UberATG on Inside a Self-Driving Uber).
QCon.ai is designed as a deep dive AI, machine learning, and data engineering conference specifically for software engineers, architects, and technical managers who see the trend of machine learning affecting all aspects of software and want to get ahead of the curve. This is a practical AI and ML conference bringing together technical engineers who want to uncover how to apply real-world use cases of machine learning in software.
QCon.ai returns to San Francisco, over April 15 - 17, 2019, and features four optional workshops in addition to the two conference days.
Registration is $1,725 ($210 off the full conference price) for the two-day conference if you register before Jan 12th!
