Javier Garza details the ingredients you need to build and deliver an app your users will love.
Cherie Wong shares common developer pain points and recipes to solve them using AWS.
Renee Orser explains how to monitor the human networks within your engineering teams using models similar to your distributed technology systems.
Kris Nova looks at the four metrics that help you decide if running stateful applications in Kubernetes is worth the risk.
Natalie Silvanovich discusses the link between feature complexity, developer error, and security vulnerabilities.
Cory Doctorow says the right to configure technology is the signature right of the 21st century.
Cory Doctorow fields questions on the future of the web, privacy, and net neutrality.
Scott Davis explains why accessibility should be just as important to you as a mobile design strategy was 10 years ago.
Tamar Bercovici details how the team at Box has constructed its database stack to handle an ever-growing query load and data set.
Lin Clark explains what browser vendors need to do over the next few years to ensure their browsers, and the web itself, meet upcoming demands.
Security Papers, Science AI, Deliberation, and Doing Science
A look at a few ways to evaluate whether or not a design achieves what it set out to do.
Practical advice for software engineers and security consultants.
The benefits of modeling data as events as a mechanism to evolve our software systems.
Taking blockchain technology private for the enterprise.
How to identify when a fit has been achieved, and how to exit the explore stage and start exploiting a product with its identified market.
Text2Binary, GraphQL, USB, and Debugging
An overview of common design patterns for navigation that will ensure users can find and use features in an application.
An overview and framework, including tools that can be used to enable automation.
Tiny Machine Learning, Deep Video, Software 2.0, and Smart Camera
Representative Recognition, Cyberwar, Data Science Projects, and Conversational Failure
The O’Reilly Data Show Podcast: Ashok Srivastava on the emergence of machine learning and AI for enterprise applications.
Algorithmic Accountability, Killing Project Maven, AI Scares Past, and Submarine Data Center
Find new ways to gain insight into how your users interact.
Cast your vote for the top open source projects and communities through June 29.
Use cases of AI and ML to help businesses build better defenses today and in the near future.
Future Analytics, Personal Data, Wireless Power, Counterintuitive Probability
Get hands-on training in machine learning, Python, Java, Kubernetes, product management, and many other topics.
This collection of AI resources will get you up to speed on the basics, best practices, and latest techniques.
The O’Reilly Podcast: Tammy Butow and Annie Lau on the importance of creating a culture of learning.
Why model development does not equal software development.
Considerations based on experience with Fortune 500 clients.
Reinforcement Learning Notebooks, Music Translation, Service Fabric, and Nat Friedman
Infinite Walking, Security Class, Collaborative Data Structures, and Brain Class
When we finally find the best use cases for blockchains, they may look like nothing we would have expected.
Internet Trends, Deep Learning, Governing Commons, and Invisible Asymptotes
Rapidly Learning Games, Geo Toolbox, Philosophy and CS, and Moravec's Paradox
Learn design best practices and where conversational AIs are headed in the future.
A commitment to multi-modal learning is better than grasping for single-modality solutions that don’t deliver.
Data Beats Algorithms, Copyright Futures, Data Privacy, and Cryptocurrency Attacks
Hypergrowth, Metaphor-Oriented Programming, Zombie Data, and Science Robotics Challenges
Recipes that deal with various aspects of troubleshooting, from debugging pods and containers, to testing service connectivity, interpreting a resource’s status, and node maintenance.
Bitcoin Badness, True Platform, Hardware Details, and Continuous Game of Life
Ben Brown on why messaging design will become as important as responsive design.
Having worked in both research and industry, Mikio Braun shares insights into what's the same, what's different, and how deep learning might change the game.
Zubin Siganporia explains how the KISS principle (“Keep It Simple, Stupid”) applies to solving problems and convincing end-users to adopt data-driven solutions to their challenges.
Martha Lane Fox considers the unintended consequences of technology.
Louise Beaumont explores the five characteristics of companies that choose to succeed.
Christine Foster discusses how today’s academic papers turn into tomorrow’s data science.
One of our goals is to bring Jupyter’s enterprise use cases and practices into one place.
The O’Reilly Data Show Podcast: A special episode to mark the 100th episode.
Successful projects will think seriously about what blockchains mean, and how to use them effectively.
The personal robot temi refactors robotic human behaviors we encounter in the “iPhone Slump,” and moves those back to actual robots.
Biosynthesising Nanomaterials, OS X Age, Debugging Machine Learning, and Deepfake Detection
Tips for creating corporate education programs through applied learning techniques.
Eva Kaili outlines the fundamentals of GDPR and applications of blockchain.
Watch highlights covering machine learning, GDPR, data protection, and more. From the Strata Data Conference in London 2018.
Ben Lorica looks at the problems we’re facing as we collect and store data, particularly when our machine learning models require huge amounts of labeled data.