Lean UX begins with the idea that user experience design should be a collaborative process.
General intelligence or creativity can only be properly imagined if we peel away the layers of abstractions.
New survey results highlight the ways organizations are handling machine learning's move to the mainstream.
These studies provide a foundation for discussing ethical issues so we can better integrate data ethics in real life.
Achieve high-impact systems monitoring by focusing on latency, errors, throughput, utilization, and blackbox monitoring.
Get advice and insight from speakers who have tackled the challenges you face.
The O’Reilly Data Show Podcast: Chang Liu on operations research, and the interplay between differential privacy and machine learning.
Principles help you align your team quickly around a shared set of product guidelines.
Practical examples of how to integrate personal and tool-based feedback into your code review process.
Tools to fine-tune the wording, formatting, and other aspects of conversation to render rich interactions.
DNA holds the key to storing vast amounts of digital data
We can build a future we want to live in, or we can build a nightmare. The choice is up to us.
The program for our Artificial Intelligence Conference in London is structured to help companies that are still very much in the early stages of AI adoption.
Strategies for assisting users in their journey to find information.
Product design is not a linear process. It’s a set of tools.
Five framing guidelines to help you think about building data products.
Recognizing the interest in ML, the Strata Data Conference program is designed to help companies adopt ML across large sections of their existing operations.
By being intentional and deliberate in your approach, you can build an excellent user experience that performs well regardless of screen size.
Jerome Hardaway explains how Vets Who Code uses open source to create job opportunities for veterans.
Mahdi Yusuf discusses new ways to unlock potential from the data you generate with smart health devices.
Roger Magoulas shares insights about the open source tools ecosystem based on analysis of usage and search data from O'Reilly's learning platform.
Sarah Novotny outlines two reasons why open source continues to be important: choice and infrastructure.
Patricia Posey draws on her non-traditional journey into tech to illustrate how honest investments can build a sustainable community that is integral to the advancement of its members.
Jay Gambetta explores Qiskit, an open-source framework that aims to make quantum computing accessible for everyone.
Angie Brown explains how Home Depot uses open source in its stores, online search, order management, analytics, and more.
The O’Reilly Open Source Awards recognize individual contributors who have demonstrated exceptional leadership, creativity, and collaboration in the development of open source software.
Measuring each stage of the user journey allows you to measure conversions and improve user experience.
The O’Reilly Data Show Podcast: Andrew Feldman on why deep learning is ushering a golden age for compute architecture.
Ying Xiong explains how Huawei collaborates with industry leaders and innovates through open source projects.
Christopher Ferris says Hyperledger was formed to help deliver blockchain technology for the enterprise. Two and a half years later, that goal is being realized.
Watch highlights covering open source, AI, cloud, and more. From the O'Reilly OSCON Conference in Portland 2018.
Camille Eddy explains what we can do to create culturally sensitive computer intelligence and why that's important for the future of AI.
Suz Hinton live codes an entertaining hardware solution in front of your eyes.
Tim O'Reilly looks at how we can extend the values and practices of open source in the age of AI, big data, and cloud computing.
Zaheda Bhorat explores the next wave of open source contributions.
While models and algorithms garner most of the media coverage, this is a great time to be thinking about building tools in data.
The basic technology behind gene editing and a conversation between Jennifer Doudna and Siddhartha Mukherjee.
An overview of the challenges MLflow tackles and a primer on how to get started.
Oaths have their value, but checklists will help put principles into practice.
O’Reilly Media Podcast: George Miranda discusses the benefits and challenges of a service mesh, and the best ways to get started using one.
Get a basic overview of data engineering and then go deeper with recommended resources.
How to use research to organize information intuitively.
Techniques for defining a product and building and managing a team.
“Human in the loop” software development will be a big part of the future.
Data scientists, data engineers, AI and ML developers, and other data professionals need to live ethical values, not just talk about them.
Learn why this new tool is a critical component in microservice-based architectures.
The clearest path to a product management role is at your current organization.
It's all about building an MVP.
The O’Reilly Data Show Podcast: Aurélie Pols on GDPR, ethics, and ePrivacy.
Explore TensorFlow’s applications and its community on July 17 at TensorFlow Day at OSCON.
Product managers are in hot demand and have myriad career options, from executive management to solutions consulting to just staying put.
We should take the impact our designs have on others' lives as seriously as we take the need for profit and competitive advantage.
Progressive organizations know that learning is as much about recruitment and retention as it is about development.
The importance of testing your tools, using multiple tools, and seeking consistency across various interpretability techniques.
It’s easy to imagine an AI winning a game of Go, but can you imagine an AI wanting to play a game of Go?
How sprints can help separate the good ideas from the bad.
The most successful product managers quickly develop three domains of knowledge: organizational, product, and industry.
The O’Reilly Data Show Podcast: Andrew Burt and Steven Touw on how companies can manage models they cannot fully explain.
We need to build organizations that are self-critical and avoid corporate self-deception.
Oracle's Kyle York and Netra's Richard Lee discuss Netra’s high-performance computing environment.