PDF to Data Frame, Clever Story, Conceptual Art, and Automatic Patch Synthesis
Git Playbook, Lessons Learned, Neural NLP, and Landscape Generation
O’Reilly’s new survey reveals the latest operations salary trends, and the skill sets that will keep your operations career on track.
Reservoir Computing, ProxyJump, SID Sequencer, and 2KB AI
Common Sense, Photorealistic Rendering, Logic Game, and the Grey-hat Patcher
Create a coherent BI strategy that aligns data collection and analytics with the general business strategy.
Robots, Cryptocurrencies, Bayes, and Brains
This collection of serverless resources will get you up to speed on the basics and best practices.
Kristian Hammond maps out simple rules, useful metrics, and where AI should live in the org chart.
Supasorn Suwajanakorn discusses the possibilities and the dark side of building artificial people.
Decentralized Applications, Global Startups, Better Shuffling, and Prolog Text
Marc Warner and Louis Barson discuss the internal and external uses of AI in the UK government.
Jason Knight offers an overview of the state of the field for scaling training and inference across distributed systems.
Cassie Kozyrkov shares machine learning lessons learned at Google and explains what they mean for applied data science.
Drawing on the McKinsey Global Institute’s research, Michael Chui explores commonly asked questions about AI and its impact on work.
The O’Reilly Data Show Podcast: Jacob Ward on the interplay between psychology, decision-making, and AI systems.
Ben Lorica and Roger Chen highlight recent trends in data, compute, and machine learning.
Ruchir Puri explains why trust and transparency are essential to AI adoption.
Amy Heineike explains how Primer created a self-updating knowledge base that can track factual claims in unstructured text.
Watch highlights from expert talks covering artificial intelligence, machine learning, automation, and more.
Yangqing Jia talks about what makes AI software unique and its connections to conventional computer science wisdom.
Ian Massingham discusses the application of ML and AI within Amazon, from retail product recommendations to the latest in natural language understanding.
Jonathan Ballon explains why Intel’s AI and computer vision edge technology will drive advances in machine learning and natural language processing.
Ashok Srivastava draws upon his cross-industry experience to paint an encouraging picture of how AI can solve big problems.
Better Education, Do You Need Blockchain?, Visualization Book, and Hiring Coders
Our bad AI could be the best tool we have for understanding how to be better people.
Lost Lessons, Metaphors to Monads, Future of Work, and Awesome Starts at The Top
Stripe Stats, Worker Ethics, FPGA Futures, and Internet Archive Stats
Supply Chain Security, ML in FB Marketplace, Datasette Ideas, and Scraper DSL
Autonomy and UI, Replicating ML Research, FPGA Dev, and Standard Notes
A new report examines the state of infrastructure and anticipated near-term developments through the eyes of infrastructure experts.
Laura Thomson shares Mozilla’s approach to data ethics, review, and stewardship.
Roger Magoulas shares insights from O'Reilly's online learning platform that point toward shifts in the systems engineering ecosystem.
Tammy Butow explains how companies can use Chaos Days to focus on controlled chaos engineering.
Jaana Dogan explains why Google teaches its tracing tools to new employees and how it helps them learn about Google-scale systems end to end.
Michael Bernstein offers an unflinching look at some of the fallacies that developers believe about marketing.
Practical techniques to ensure developers can actually do the things you want them to do using your API.
Positive Chatbot, Inside Serverless, TimBL's Next Project, and Voting Machines
Get hands-on training in machine learning, Python, Kubernetes, blockchain, security, and many other topics.
Watch highlights from expert talks covering DevOps, SRE, security, machine learning, and more.
Anil Dash asks: How could our processes and tools be designed to undo the biggest bugs and biases of today’s tech?
Kris Beevers examines the trade-offs between risk and velocity faced by any high-growth, critical path technology business.
Jessica McKellar draws parallels between the free and open source software movement and the work to end mass incarceration.
Francesc Campoy Flores explores ways machine learning can help developers be more efficient.
Laurent Gil shares the latest cybersecurity research findings based on real-world security operations.
Dave Rensin explains why DevOps and SRE make each other better.
Kavya Joshi says performance theory offers a rigorous and practical approach to performance tuning and capacity planning.
Apple MDM, Source Explorer, Verification-Aware Programming, and Superstar Economics
DARPA History, Probabilistic Programming, Superstar Macroeconomics, and Interactive Narrative
How risk reduction makes sure bad things happen as rarely as possible.
Observing Kubernetes, Ada Lovelace, Screen Time, and 6502 C
The O’Reilly Data Show Podcast: Sharad Goel and Sam Corbett-Davies on the limitations of popular mathematical formalizations of fairness.
Calendar Fallacies, Data Lineage, Firefox Monitor, and Glitch Handbook
The World Economic Forum’s 2018 jobs report limits research to a narrow range of the workforce.
Walmart's Blockchain, Machine Learning and Text Adventures, Algorithmic Decision-Making, and Networked Brains
Software Engineering, ML Hardware Trends, Time Series, and Eng Team Playbooks
Getting DataOps right is crucial to your late-stage big data projects.
Continuous Delivery, Turing Complete Powerpoint, ARPA-E, and Observability
How we can put privacy at the heart of our design processes.