Data governance: What you need to know
An ongoing data governance program provides intellectual and institutional grounding to adhere to a company's strategic plan.
Data
Our take on the ideas, information, and tools that make data work.
Building machine learning solutions that can withstand adversarial attacks
The O’Reilly Data Show Podcast: Parvez Ahammad on minimal supervision, and the importance of explainability, interpretability, and security.
Why you need a data strategy, and what happens if you don’t have one
How to map out a plan for finding value in data.
Deep learning for Apache Spark
The O’Reilly Data Show Podcast: Jason Dai on BigDL, a library for deep learning on existing data frameworks.
The state of Jupyter
How Project Jupyter got here and where we are headed.
The key to building deep learning solutions for large enterprises
The O’Reilly Data Show Podcast: Adam Gibson on the importance of ROI, integration, and the JVM.
Putting the science back in data science
Best practices and scalable workflows for reproducible data science.
How big compute is powering the deep learning rocket ship
The O’Reilly Data Show Podcast: Greg Diamos on building computer systems for deep learning and AI.
The 2017 machine learning outlook
Drew Paroski and Gary Orenstein on the rapid spread of machine learning and predictive analytics
8 data trends on our radar for 2017
From deep learning to decoupling, here are the data trends to watch in the year ahead.
2017 will be the year the data science and big data community engage with AI technologies
The O’Reilly Data Show Podcast: A look at some trends we’re watching in 2017.
Data is only as valuable as the decisions it enables
The O’Reilly Data Show Podcast: Ion Stoica on building intelligent and secure applications on live data.
Reinforcement learning explained
Learning to act based on long-term payoffs.
Introducing model-based thinking into AI systems
The O’Reilly Data Show Podcast: Vikash Mansinghka on recent developments in probabilistic programming.
Building the next-generation big data analytics stack
The O’Reilly Data Show Podcast: Michael Franklin on the lasting legacy of AMPLab.
The hard thing about deep learning
Deeper neural nets often yield harder optimization problems.
Visual tools for overcoming information overload
The O’Reilly Data Show Podcast: Dafna Shahaf on information cartography and AI, and Sam Wang on probabilistic methods for forecasting political elections.
The big data ecosystem for science
A look at the data pipeline architecture for five key NERSC projects.
Why businesses should pay attention to deep learning
The O’Reilly Data Show Podcast: Christopher Nguyen on the early days of Apache Spark, deep learning for time-series and transactional data, innovation in China, and AI.
Understanding predictive analytics
The O’Reilly Data Show Podcast: Natalino Busa on developments in feature engineering and predictive techniques across industries.
The technology behind self-driving vehicles
The O’Reilly Data Show Podcast: Shaoshan Liu on perception, knowledge, reasoning, and planning for autonomous cars.
Highlights from Strata + Hadoop World in New York 2016
Watch highlights covering data science, big data, data in the enterprise, and more. From Strata + Hadoop World in New York 2016.
Inbox is the Trojan horse of AI
Alistair Croll looks at the sometimes surprising ways that machine learning is insinuating itself into our every day lives.
The tech behind the biggest journalism leak in history
Mar Cabra explains how technology made the Panama Papers investigation possible.