The quest to evolve neural networks through evolutionary algorithms.
A tutorial on how to use machine learning to build recommender systems.
The O’Reilly Data Show Podcast: David Talby on a new NLP library for Spark, and why model development starts after a model gets deployed to production.
Learn about some of the common issues you will encounter when developing algorithms for a modern anomaly detection system.
A deep dive into Uber's engineering effort to optimize geospatial queries in Presto.
Probabilistic computation holds too much promise for it to be stifled by playing zero sum games with data.
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Watching the appeal and applications of machine intelligence expand.
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The adventures in deep learning and cheap hardware continue!
June Andrews talks about simple, cost-effective algorithmic computing at scale.
Working with uncertainty in real-world data.
How to build a class of RL agents using a TensorFlow notebook.
Mike Barlow examines the growth of sophisticated cloud-based AI and machine learning services for a growing market of developers and users in business and academia.
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