InfoQ Homepage AI, ML & Data Engineering Content on InfoQ
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Self-Racing Using Deep Neural Networks: Lap 2
Jendrik Joerdening and Anthony Navarro discuss how a team of Udacity students used neural networks to teach a car to drive by itself around a track in two days.
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The Black Swan of Perfectly Interpretable Models
Mayukh Bhaowal, Leah McGuire discuss how Salesforce Einstein made ML more transparent and less of a black box, and how they managed to drive wider adoption of ML.
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Counting is Hard: Probabilistic Algorithms for View Counting at Reddit
Krishnan Chandra explains the challenges of building a view counting system at scale, and how Reddit used probabilistic counting algorithms to make scaling easier.
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Developing Data and ML Pipelines at Stitch Fix
Jeff Magnusson discusses thoughts and guidelines on how Stitch Fix develops, schedules, and maintains their data and ML pipelines.
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Cloud-Native Data: What Is it? Will it Solve the Data-DevOps Divide?
The panelists debate whether data's answer to cloud-native will mirror DevOps or not.
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Counterfactual Evaluation of Machine Learning Models
Michael Manapat discusses how Stripe evaluates and trains their machine learning models to fight fraud.
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Machine Learning Pipeline for Real-Time Forecasting @Uber Marketplace
Chong Sun and Danny Yuan discuss how Uber is using ML to improve their forecasting models, the architecture of their ML platform, and lessons learned running it in production.
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Using Artificial Intelligence to Test the Candy Crush Saga Game
Alexander Andelkovic shows how King is training artificial intelligence bots to test its games by mimicking human interactions.
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Streaming Reactive Systems & Data Pipes w. Squbs
Anil Gursel and Akara Sucharitakul focus on modeling and building software that considers all input and all output as stream of events, and introducing Squbs.
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Streaming SQL Foundations: Why I ❤ Streams+Tables
Tyler Akidau explores the relationship between the Beam Model and stream & table theory and explains what is required to provide robust stream processing support in SQL.
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Next Steps in Stateful Streaming with Apache Flink
Stephan Ewan talks about how Apache Flink is making stateful stream processing even more expressive and flexible to support applications in streaming that were previously not considered streamable.
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Drivetribe: A Social Network on Streams
Aris Koliopoulos talks about how common problems in social media can be resolved with a healthy mix of stream processing and functional programming.
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