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Tracy Ferrell and Phil Beevers on the principles of Site Reliability Engineering and successful SRE teams.
Get a comprehensive overview and hands-on training on software architecture's many aspects.
Get a basic understanding of serverless, then go deeper with recommended resources.
Our most-used Java resources will help you stay on track in your journey to learn and apply Java.
Automated pet herding for fun and profit.
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Three reasons why confidence intervals should not be used in financial data analyses.
Katacoda’s interactive learning scenarios and sandboxes will help O’Reilly users master important technologies.
Thoughtful and effective decision-making was a key trend at the O’Reilly Software Architecture Conference in Berlin 2019.
Every business that relies on technology is facing an infrastructure upheaval.
Experts explore new trends, tools, and techniques in software architecture.
Experts explore new trends, tools, and techniques in systems engineering and cloud native systems.
Watching the O'Reilly teams accept the challenge of the Kincade fire and subsequent power outages was nothing short of remarkable.
Experts explore TensorFlow 2.0's machine learning capabilities as well as the broader tools and applications of TensorFlow.
Experts explore AI's most promising developments, emerging technologies, and profitable use cases.
The O’Reilly Data Show Podcast: Peter Bailis on data management, ML benchmarks, and building next-gen tools for analysts.
Java is ready for the cloud today.
Paige Bailey, TensorFlow product manager at Google, highlights notable features of TensorFlow 2.0 and looks ahead to near-term updates.
The O’Reilly Data Show Podcast: Arun Kejariwal and Ira Cohen on building large-scale, real-time solutions for anomaly detection and forecasting.
Experts explore new trends, tools, and techniques in data and machine learning.
AI startups vied for awards at the O’Reilly Artificial Intelligence Conference in San Jose.
Experts discuss new trends, tools, and issues in artificial intelligence and machine learning.
The O’Reilly Data Show Podcast: Michael Mahoney on developing a practical theory for deep learning.
New editions of Four Short Links are available at oreilly.com/radar.
Machine learning, artificial intelligence, data engineering, and architecture are driving the data space.
Distributed Consistency, Face Anonymization, Game Mechanic Discovery, and Images of Images
Mapping Values, Crawlers are Legal, Laser Tripwire, and Coercion-Resistant Design
Get a basic understanding of Kubernetes and then go deeper with recommended resources.
Secure Android, Group Chats, Ethical Location Data, and Philosophy of Computer Science
Code Reviews, Dogfooding, Deobfuscation, and Differential Privacy
Cultural Competency, Computer-Generated Sound, Bottom-Up CS, and Continuous Compliance
A look at why graphs improve predictions and how to create a workflow to use them with existing machine learning tasks.
iOS Security, IoT Wi-Fi Attacks, Interactive SSH Programs, and Replacing Faces in Video
An overview of applications of new tools for overcoming silos, and for creating and sharing high-quality data.
Crummy Translations, Synthetic Data Sets, Building Communities, and Deleting Accounts
Enigma Simulator, Robot Startups, Code as Type, and Conversational Modeling
Multi-Language Teams, AI Release Models, Security Myth, and The Internet is for End Users
The O’Reilly Data Show Podcast: Kesha Williams on how she added machine learning to her software developer toolkit.
Debugging a Scale Problem, Verifying Cryptographic Protocols, Remote Team Stress, and PAC-MAN Source
Multi-layer architecture, scalability, multitenancy, and durability are just some of the reasons companies have been using Pulsar.
Tech and Politics, Crypto-Mining Malware, Cost of Securing DNS, and Anti-Fuzzing Techniques
Personal Information, Research Data, Massive Lamba Scale, and The Moral Character of Cryptographic Work
Avoiding Sexual Predators, YouTube Radicalization, Brian Behlendorf, and Cyberpunk Present
To successfully implement AI technologies, companies need to take a holistic approach toward retraining their workforces.
Open Source Economics, Program Synthesis, YouTube Influence, and ChatBot Papers
I Don't Know, Map Quirks, UI Toolkit, and Open Power Chip Architecture
Competition vs. Convenience, Super-Contributors and Power Users, Forecasting Time Series, and Appreciating Non-Scalability
Content Moderation, Robust Learning, Archiving Floppies, and xkcd Charting
Developer Tool, Deep Fakes, DNA Tests, and Retro Coding Hacks
What we really need is disclosure of information about the growth and health of the supply side of Big Tech's marketplaces.
The O’Reilly Data Show Podcast: Alex Ratner on how to build and manage training data with Snorkel.
Data Businesses, Data Science Class, Tiny Mouse, and Training Bias
Hardware Deplatforming, Hiring Groupthink, Loot Boxes and Problem Gambling, and Interoperability and Privacy
Recognizing Fact, YouTube & Brazil, Programming Zine, and Credit Blacklists
Retro Hacking, Explaining AI, Teacher Ratings, and Algorithmic Bias
A review of the crucial steps for a successful blockchain-based solution.
Shadow Ban Patent, Abusing Unix Tools, Deblurring Photos, and Postal Vectors
Speech adds another level of complexity to AI applications—today’s voice applications provide a very early glimpse of what is to come.