Specialized hardware for deep learning will unleash innovation
The O’Reilly Data Show Podcast: Andrew Feldman on why deep learning is ushering a golden age for compute architecture.
Data
Our take on the ideas, information, and tools that make data work.
Of oaths and checklists
Oaths have their value, but checklists will help put principles into practice.
Doing good data science
Data scientists, data engineers, AI and ML developers, and other data professionals need to live ethical values, not just talk about them.
Data regulations and privacy discussions are still in the early stages
The O’Reilly Data Show Podcast: Aurélie Pols on GDPR, ethics, and ePrivacy.
Managing risk in machine learning models
The O’Reilly Data Show Podcast: Andrew Burt and Steven Touw on how companies can manage models they cannot fully explain.
The blockchain beyond bitcoin
Taking blockchain technology private for the enterprise.
The real value of data requires a holistic view of the end-to-end data pipeline
The O’Reilly Data Show Podcast: Ashok Srivastava on the emergence of machine learning and AI for enterprise applications.
Lessons learned turning machine learning models into real products and services
Why model development does not equal software development.
When to KISS
Zubin Siganporia explains how the KISS principle (“Keep It Simple, Stupid”) applies to solving problems and convincing end-users to adopt data-driven solutions to their challenges.
Out of the lab and into real life
Christine Foster discusses how today’s academic papers turn into tomorrow’s data science.
The good, the bad, and the internet?
Martha Lane Fox considers the unintended consequences of technology.
So, you want to be successful in the open future?
Louise Beaumont explores the five characteristics of companies that choose to succeed.
Machine learning: Research & industry
Having worked in both research and industry, Mikio Braun shares insights into what's the same, what's different, and how deep learning might change the game.
The evolution of data science, data engineering, and AI
The O’Reilly Data Show Podcast: A special episode to mark the 100th episode.
Highlights from the Strata Data Conference in London 2018
Watch highlights covering machine learning, GDPR, data protection, and more. From the Strata Data Conference in London 2018.
Charting a data journey to the cloud
Mick Hollison, Sven Löffler, and Robert Neumann explain how Deutsche Telekom is harnessing machine learning and analytics in the cloud to build Europe’s largest IoT data marketplace.
Journey to GDPR compliance
May 25 is an important day for data protection in the EU and elsewhere. Alison Howard explains how Microsoft has prepared for May 25 and beyond.
Building a stronger data ecosystem
Ben Lorica looks at the problems we’re facing as we collect and store data, particularly when our machine learning models require huge amounts of labeled data.
The Paradise Papers: Behind the scenes with the ICIJ
Pierre Romera explores the challenges in making 1.4 TB of data securely available to journalists all over the world.
Data protection and innovation
Eva Kaili outlines the fundamentals of GDPR and applications of blockchain.
How will the GDPR impact machine learning?
Answers to the three most commonly asked questions about maintaining GDPR-compliant machine learning programs.
Companies in China are moving quickly to embrace AI technologies
The O’Reilly Data Show Podcast: Jason Dai on the first year of BigDL and AI in China.
Teaching and implementing data science and AI in the enterprise
The O’Reilly Data Show Podcast: Jerry Overton on organizing data teams, agile experimentation, and the importance of ethics in data science.
The importance of transparency and user control in machine learning
The O’Reilly Data Show Podcast: Guillaume Chaslot on bias and extremism in content recommendations.