Machine learning (ML) isn’t new. However, the field of big data is revitalizing the subject and more organizations are relying on ML models to scale their operations, support staff in working better and faster, to uncover hidden insights from data, or even confirm and challenge underlying assumptions. This is creating widespread interest in related topics with the C-suite, and across business lines and job roles, as enterprises embrace the value of artificial intelligence (AI) and ML.
To make a disruptive organizational impact, AI and ML need to be understood and trusted. By consulting these ML blogs from authoritative individuals and organizations that satisfy different skill levels, readers can increase their understanding and comfort level in these areas, get pressing questions answered, and connect with others who have experience using them to great benefit.
OpenAI comes from industry experts who want to bring AI to the masses. It’s linked to the non-profit research company OpenAI, co-chaired by Elon Musk and Sam Altman, and sponsored by companies such as Amazon Web Services, Microsoft, and Infosys who are trying to make AI accessible—hence the name. Contributors discuss their collective efforts to promote and advance AI technologies through long-term research. It’s a valuable resource for anyone interested in the future of AI.
Managed by: Shan Carter, Chris Olah, and Arvind Satyanarayan
Distill concentrates on making ML and AI more accessible for readers. Traditional research can be difficult to consume, so Distill communicates ML research in appealing, interactive data visualizations. It acts as a neutral platform for multiple authors to publish together, and articles are peer-reviewed, appearing in Google Scholar. Distill is also registered with the Library of Congress and CrossRef.
Authored by: Adam Geitgey
Machine Learning is Fun is a valuable, introductory blog. It covers the tenets of ML through interactive tutorials and practical examples, which make it easier to see the useful applications to different businesses and industries. Author Adam Geitgey is a former software developer who now consults organizations on implementing machine learning. He believes ML is integral to the future of software and that developers should have a strong working knowledge, so he provides guides and techniques to help them develop and grow.
Authored by: Jason Brownlee
A machine learning developer with several AI-related degrees, Jason intended his Machine Learning Mastery blog for new developers getting started in the field. He was once an amateur developer and wants to help others, imparting lessons learned during his professional journey and sharing the tools that helped him most. The blog, plus his email course and newsletter, accommodate any level of expertise.
Managed by: Berkeley Artificial Intelligence Research
The artificial intelligence research department at UC Berkeley created this blog to convey research findings and important information about their AI-related work. Covering a spectrum of research—from natural language processing to robotics—grad students and faculty contribute content for both experts and the general population to consume.