The O’Reilly Data Show Podcast: Haoyuan Li on accelerating analytic workloads, and innovation in data and AI in China.
Raw Data, Learning Text Adventures, Algorithms Textbook, and Physical Computing
Robot Cafe, Surveillance Sci-Fi, Hardware is Hard, and UI Typeface
Amazon Tricks, Public Domain, Blocking Telegram, and Approximate Spreadsheets
Schema Crawler, Open Source Bug Bounties, Essential C, and AI Poker
Bayes Notes, Fake Internet, Tensorflow Privacy, Sortable UUIDs
Reading Minds, Year Gotchas, LSTM Conversation, and Fast Scanning
Evil FizzBuzz, Atari OS, Logic Guide, and Artificial Life
Hardware Testing is Hard, Biological Keygen, Christmas Robots, and Open Data
Learning Prolog, Data Race, Animating Photos, and Easy Flashing
Tech in China, Wisdom of Small Groups, iOS VPN, and Gameboy Supercomputer
The O’Reilly Data Show Podcast: Ben Lorica looks ahead at what we can expect in 2019 in the big data landscape.
Misinformation Research, AI UI, Facebook's Value, and Python Governance
An overview of NAS and a discussion on how it compares to hyperparameter optimization.
Observable Notebooks, Disinformation Report, Chained Blocking, and Trivia from 2018
We need to do more than automate model building with autoML; we need to automate tasks at every stage of the data pipeline.
Our most-used AWS resources will help you stay on track in your journey to learn and apply AWS.
Singing AI, Content Signing, Data Rights, and Query Processing
Open Source Licensing, Computer History, Serverless, and Wicked Problems
Satellite LoRaWAN, Bret Victor, State of AI, and Immutable Documentation
CS Ethics, Insect IoT, Glitch Showcase, and SQL Repos
Render as Comic, Notebook to Production, Population Visualization, and Location Privacy
Can We Stop?, Everything Breaks, Edge Cloud, and Molly Guard
Language Zoo, VS AI, Advertising Plus, and Minecraft Scripting
Broken Feedback, Fake AI, Teaching with Jupyter, and Multiplayer Code UI
When it comes to automation of existing tasks and workflows, you need not adopt an “all or nothing” attitude.
The O’Reilly Data Show Podcast: Alex Wong on building human-in-the-loop automation solutions for enterprise machine learning.
Public Domain, Optimistic Sci-Fi, C64 Defrag, and Quantum Computing
Get a basic understanding of distributed systems and then go deeper with recommended resources.
NLP for Code, Monolith vs. Modular, Automatic Gender Recognition, and Budget Simulator
A new report explores how far companies have come with microservices.
Voice Technology, AI Summaries, Time Tracker, and Homomorphic Encryption
Amazon and OSS, Audio to Keystrokes, The New OS, and Software Sprawl
Advents are Coming, Open Source, Restricted Exports, and Misinformation Operations
Security Sci-Fi, AWS Toys, Quantum Ledger, and Insecurity in Software in Hardware
FaaS, Space as a Service, Bot Yourself, and Facebook's RL Platform
Open Source, Interactive Fiction, Evolving Images, and Closed Worlds
Graphics Engine, Graph Library, Docker Tool, and Probabilistic Cognition
Chinese iPhone Users, Sci-Fi UI, MITM Framework, and HTTP/3
XOXO Talks, Git Illustrated, Post-REST Services, and Learning Projects
The O’Reilly Data Show Podcast: Vitaly Gordon on the rise of automation tools in data science.
Black Mirror, Innovation Toolkits, Code-Generator for APIs, and Hardware Effects
East African ML Needs, Autonomy Corrections, Information Security, and UIs from Doodles
Partial Time, Black Mirror, Implant Usability, and Open Source Game
Our most-used Java resources will help you stay on track in your journey to learn and apply Java.
Illuminated Paper, Software Forge, Leak Checklist, and PC on ESP
Punish Online Criminals, Fake Fingerprints, Implementing Identity, and Project Visbug
ML Risk, IGF Session, Feature Engineering, and Solving Snake
Ways of Working, Too-Smart AI, Wi-Fi Vision, and Materials Science AI
Considerations for a world where ML models are becoming mission critical.
Gov Open Source, Bruce Sterling, Robot Science, and Illustrated TLS 1.3
Counting Computers, New Software, Unix History, and Tencent Framework
The O’Reilly Data Show Podcast: Francesca Lazzeri and Jaya Mathew on digital transformation, culture and organization, and the team data science process.
Approximate Graph Pattern Mining, Ephemeral Containers, SaaS Metrics, and Edge Neural Networks
Summarizing Text, Knowledge Database, AI Park, and Approximate Regexes
Understanding how the Kubernetes scheduler makes scheduling decisions is critical to ensure consistent performance and optimal resource utilization.
People Don't Change, Open Access, Event Database, and Apple Maps
Probabilistic Model Checker, Notebooks to Docs, AWS 12-Factor Apps, and AI Physicist
Jane Adams examines the ways data-driven recruiting fails to achieve intended results and perpetuates discriminatory hiring practices.
Claire Janisch looks at some of the best biomimicry opportunities inspired by nature’s software and wetware.