Building data science capacity in your organization
Shingai Manjengwa shares insights from teaching data science to 300,000 online learners.
Our take on the ideas, information, and tools that make data work.
Shingai Manjengwa shares insights from teaching data science to 300,000 online learners.
Chris Taggart explains the benefits of “white box data” and outlines the structural shifts that are moving the data world toward this model.
Sandra Wachter argues that a right to reasonable inferences could protect against new forms of discrimination.
Drawing insights from recent surveys, Ben Lorica analyzes important trends in machine learning.
Cait O’Riordan discusses the North Star metric the Financial Times uses across the organization to drive subscriber growth.
Mick Hollison describes why hybrid and multi-cloud is the future for organizations that want to capitalize on machine learning and AI.
James Burke asks if we can use data and predictive analytics to take the guesswork out of prediction.
Cassie Kozyrkov explains how organizations can extract more value from their data.
Watch highlights from expert talks covering machine learning, predictive analytics, data regulation, and more.
The O’Reilly Data Show Podcast: Neelesh Salian on data lineage, data governance, and evolving data platforms.
Balancing risk and reward is a necessary tension we'll need to understand as we continue our journey into the age of data.
The O’Reilly Data Show Podcast: Avner Braverman on what’s missing from serverless today and what users should expect in the near future.
Watch highlights from expert talks covering AI, machine learning, data analytics, and more.
Peter Singer explores the new rules of power in the age of social media and how we can navigate a world increasingly shaped by "likes" and lies.
Lauren Kunze discusses lessons learned from an analysis of interactions between humans and chatbots.
Google BigQuery co-creator Jordan Tigani shares his vision for where cloud-scale data analytics is heading.
The Strata Data Award is given to the most disruptive startup, the most innovative industry technology, the most impactful data science project, and the most notable open source contribution.
Elizabeth Svoboda explains how biosensors and predictive analytics are being applied by political campaigns and what they mean for the future of free and fair elections.
Mike Olson describes the key capabilities an enterprise data cloud system requires, and why hybrid and multi-cloud is the future.
Theresa Johnson outlines the AI powering Airbnb’s metrics forecasting platform.
The O’Reilly Data Show Podcast: Forough Poursabzi Sangdeh on the interdisciplinary nature of interpretable and interactive machine learning.
Shafi Goldwasser explains why the next frontier of cryptography will help establish safe machine learning.
Jed Dougherty plots AI examples on a matrix to clarify the various interpretations of AI.
Dinesh Nirmal shares a data asset framework that incorporates current business structures and the elements you need for an AI-fluent data platform.