Getting DataOps right is crucial to your late-stage big data projects.
Using advanced Docker Compose features to solve problems in larger projects and teams.
The economy we want to build must recognize increasing the value to and for humans as the goal.
Exploring use cases for the two tools.
Asking good design questions will elucidate problems and opportunities.
Brain-based human-machine interfaces: New developments, legal and ethical issues, and potential uses
Amanda Pustilnik highlights potential applications of data from new technologies that capture brain-based processes.
Chad Jennings explains how Geotab's smart city application helps city planners understand traffic and predict locations of unsafe driving.
Ben Sharma shares how the best organizations immunize themselves against the plague of static data and rigid process
Amber Case covers methods product designers and managers can use to improve interactions through an understanding of sound design.
Dinesh Nirmal explains how AI is helping supply school lunch and keep ahead of regulations.
Ziya Ma discusses how recent innovations from Intel in high-capacity persistent memory and open source software are accelerating production-scale deployments.
Jacob Ward reveals the relationship between the unconscious habits of our minds and the way that AI is poised to amplify them, alter them, maybe even reprogram them.
Hilary Mason explores the current state of AI and ML and what’s coming next in applied ML.
Julia Angwin discusses what she's learned about forgiveness from her series of articles on algorithmic accountability and the lessons we all need to learn for the coming AI future.
We should invest at least as much time in understanding our customers as we do in optimizing our product development process.
The O’Reilly Data Show Podcast: Alan Nichol on building a suite of open source tools for chatbot developers.
Cassie Kozyrkov explores why businesses fail at machine learning despite its tremendous potential and excitement.
Ben Lorica offers an overview of recent tools for building privacy-preserving and secure machine learning products and services.
DD Dasgupta explores the edge-cloud continuum, explaining how the roles of data centers and cloud infrastructure are redefined through the mainstream adoption of AI, ML, and IoT technologies.
Drew Paroski and Aatif Din share how to develop modern database applications without sacrificing cost savings, data familiarity, and flexibility.
Watch highlights from expert talks covering data science, machine learning, algorithmic accountability, and more.
Executives from Cloudera and PNC Bank look at the challenges posed by data-hungry organizations.
Ted Dunning discusses how new tools can change the way production systems work.
Poll results reveal where and why organizations choose to use containers, cloud platforms, and data pipelines.
It has become much more feasible to run high-performance data platforms directly inside Kubernetes.
If we’re going to think about the ethics of data and how it’s used, then we have to take into account how data flows.
Dawn Song explains how AI and deep learning can enable better security and how security can enable better AI.
David Patterson explains why he expects an outpouring of co-designed ML-specific chips and supercomputers.
Joseph Sirosh tells an intriguing story about AI-infused prosthetics that are able to see, grip, and feel.
Peter Norvig says one of the most exciting aspects of AI is the diversity of applications in fields far astray from the original breakthrough areas.
Manish Goyal shows you how to best unlock the value of enterprise AI.
Levent Besik explains how enterprises can stay ahead of the game with customized machine learning.
Huma Abidi discusses the importance of optimization to deep learning frameworks.
Hagay Lupesko explores key trends in machine learning, the importance of designing models for scale, and the impact that machine learning innovation has had on startups and enterprises alike.
From chaos architecture to event streaming to leading teams, the O'Reilly Software Architecture Conference offers a unique depth and breadth of content.
Akhilesh Tripathi shows you how to use machine learning to identify root causes of problems in minutes instead of hours or days.
Julie Shin Choi reviews real-world customer use cases that take AI from theory to reality.
Kishore Durg explains why deploying AI requires raising it to act as a responsible representative of the business and a contributing member of society.
Tim O'Reilly and Kai-Fu Lee discuss differences in how China and the U.S. approach AI and why AI might give humanity larger purpose.
Kai-Fu Lee outlines the factors that enabled China's rapid ascension in AI.
Meredith Whittaker says the benefits of AI will only come if we have a clear-eyed perspective on its dark side.
Soups Ranjan describes the machine learning system that Coinbase built to detect potential fraud and fake identities.
Watch highlights from expert talks covering artificial intelligence, machine learning, security, and more.
A new survey highlights concerns from network and cloud administrators, and reveals their coping strategies.
This collection of data governance resources will get you up to speed on the basics and best practices.
Get hands-on training in machine learning, blockchain, Java, software architecture, leadership, and many other topics.
Data can help inform design choices at every step in the process.
The O’Reilly Data Show Podcast: Eric Jonas on Pywren, scientific computation, and machine learning.
The O’Reilly Media Podcast: Daniel Krook, IBM developer advocate, on the Call for Code Global Initiative at IBM.
Tools and techniques for recruiting UX research participants.
How the UK's NHS uses prototyping to explore and illustrate new technological possibilities.
Fernando Perez talks about UC Berkeley's transition into an environment where many undergraduates use Jupyter and the open data ecosystem as naturally as they use email.
Michelle Ufford shares how Netflix leverages notebooks today and describes a brief vision for the future.
Michelle Gill discusses how data science methods and tools can link information from different scientific fields and accelerate discovery.
Tracy Teal explains how to bring people to data and empower them to address their questions.
Cristian Capdevila explains how Prognos is predicting disease.
David Schaaf explains how data science and data engineering can work together to deliver results to decision makers.
Ryan Abernathey makes the case for the large-scale migration of scientific data and research to the cloud.
Watch keynotes covering Jupyter's role in business, data science, higher education, open source, journalism, and other domains, from JupyterCon in New York 2018.
Luciano Resende explores some of the open source initiatives IBM is leading in the Jupyter ecosystem.
Carol Willing shows how Jupyter's challenges can be addressed by embracing complexity and trusting others.