Architecting actionable insights
Bas Geerdink details the technology stack for real-time account forecasting at ING, and outlines how Spark is used for outbound communications.
Our take on the ideas, information, and tools that make data work.
Ideas
Interpretability via attentional and memory-based interfaces, using TensorFlow
A closer look at the reasoning inside your deep networks.
Data science and deep learning in retail
The O’Reilly Data Show Podcast: Jeremy Stanley on hiring and leading machine learning engineers to build world-class data products.
Ideas on interpreting machine learning
Mix-and-match approaches for visualizing data and interpreting machine learning models and results.
AI building blocks: The eggs, the chicken, and the bacon
Data, algorithms, and better business results are key to developing AI.
The stages of enterprise IoT adoption
Teresa Tung on building a business case for the Internet of Things.
2017 European Data Science Salary Survey
Tools, trends, what pays (and what doesn’t) for data professionals in Europe
The current state of machine intelligence 3.0
Watching the appeal and applications of machine intelligence expand.
Learning
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Build a super fast deep learning machine for under $1,000
The adventures in deep learning and cheap hardware continue!
Video
How Pinterest uses humans in the loop to analyze clusters
June Andrews talks about simple, cost-effective algorithmic computing at scale.
Runnable code
Repeatable sampling of data sets in BigQuery for machine learning
An efficient, fast, and repeatable selection method that works on very large data sets.
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Hello, TensorFlow!
Building and training your first TensorFlow graph from the ground up.
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Practical artificial intelligence in the cloud
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.
Training
O'Reilly live online data training
Get intensive, hands-on training on current critical data technology topics, led by instructors from O'Reilly's unparalleled network of tech innovators and expert practitioners.
Introduction to Apache Spark 2.1
Adam Breindel shows you the modern best practices for Spark 2.1, using the latest Spark features, for high-performance analytics, processing, and modeling on large-scale data sets.
Practical Data Cleaning with Python
Katharine Jarmul will show you how to use Python libraries to speed up the data wrangling process and automate data cleaning, how to handle messy data, and how to write data unit tests that monitor data validity.
Events
Sessions
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“Data is having an impact on business models and profitability. It’s hard to find a non-trivial application that doesn’t use data in a significant manner.”
— Ben Lorica, Director of Content Strategy for Data at O'Reilly Media