Resolving transactional access and analytic performance trade-offs
The O’Reilly Data Show podcast: Todd Lipcon on hybrid and specialized tools in distributed systems.
AI & ML
Few technologies have the potential to change the nature of work and how we live as artificial intelligence (AI) and machine learning (ML).
Five principles for applying data science for social good
How to go from well-intentioned efforts to lasting impact with your data projects.
Being data-driven: It’s all about the culture
Data analysis can change an organization’s future -- but only if it’s used in the present, every day, by everyone.
Building enterprise data applications with open source components
The O’Reilly Data Show podcast: Dean Wampler on bounded and unbounded data processing and analytics.
From search to distributed computing to large-scale information extraction
The O'Reilly Data Show Podcast: Mike Cafarella on the early days of Hadoop/HBase and progress in structured data extraction.
6 reasons why I like KeystoneML
The O'Reilly Data Show Podcast: Ben Recht on optimization, compressed sensing, and large-scale machine learning pipelines.
Building self-service tools to monitor high-volume time-series data
The O'Reilly Data Show Podcast: Phil Liu on the evolution of metric monitoring tools and cloud computing.
Artificial intelligence?
AI scares us because it could be as inhuman as humans.
Data science makes an impact on Wall Street
The O'Reilly Data Show Podcast: Gary Kazantsev on how big data and data science are making a difference in finance.
The tensor renaissance in data science
The O'Reilly Data Show Podcast: Anima Anandkumar on tensor decomposition techniques for machine learning.
Building big data systems in academia and industry
The O'Reilly Data Show Podcast: Mikio Braun on stream processing, academic research, and training.
Turning Ph.D.s into industrial data scientists
Angie Ma's startup, London-based ASI, runs a carefully structured “finishing school” for science and engineering doctorates.
Topic models: Past, present, and future
David Blei, co-creator of one of the most popular tools in text mining and machine learning, discusses the origins and applications of topic models.
A brief look at data science’s past and future
In this O'Reilly Data Show Podcast: DJ Patil weighs in on a wide range of topics in data science and big data.
Apache Spark’s journey from academia to industry
In this O'Reilly Data Show Podcast: Ion Stoica talks about the rise of Apache Spark and Apache Mesos.
Artificial intelligence: summoning the demon
We need to understand our own intelligence is competition for our artificial, not-quite intelligences.
Big data’s big ideas
From cognitive augmentation to artificial intelligence, here's a look at the major forces shaping the data world.
Small brains, big data
How neuroscience is benefiting from distributed computing, and how computing might learn from neuroscience.
What is deep learning, and why should you care?
Delving into deep learning and the inner workings of neural networks.
Questioning the Lambda Architecture
The Lambda Architecture has its merits, but alternatives are worth exploring.
AI’s dueling definitions
Why my understanding of artificial intelligence is different from yours.
Untapped opportunities in AI
Some of AI's viable approaches lie outside the organizational boundaries of Google and other large Internet companies.
Operations, machine learning, and premature babies
An astonishing connection between web ops and medical care.
What is data science?
The future belongs to the companies and people that turn data into products.