I’m a writer, scientist, and programmer. I’m currently taking a sabbatical to write a technical book about artificial neural networks and deep learning. The book explains how neural networks can learn to solve complex pattern recognition problems. Early beta chapters from the book are available here. Sign up here if you’d like to receive announcements […]
Search results for 'nielsen'
On Twitter, I’ve been chatting with my friend Julia Galef about tensions between thinking creatively and thinking in a way that reduces error. Of course, all other things being equal, I’m in favour of reducing error in our thinking! However, all other things are not always equal. In particular, I believe “there’s a tension, too, […]
My new essay on the use of digital media to explain scientific ideas is here.
In September of 2012, a team of scientists released a photograph showing the most distant parts of the Universe ever seen by any human being. They obtained the photograph by pointing the Hubble Space Telescope at a single tiny patch of sky, gradually building up an image over a total of 23 days of observation. […]
OSS-bot is a crawler I (Michael Nielsen) built for educational purposes — I run occasional informal meetups where programmers in Toronto get together to talk about machine learning, information retrieval, and similar topics. The crawler: (1) Is designed to be polite — it obeys robots.txt, as well as various other best practices. If you wish […]
The loose theme underlying my writing is the use of science and technology to improve the way we think. The essays I’m proudest of are The future of science, Is scientific publishing about to be disrupted?, and Lisp as the Maxwell’s equations of software. I’ve collected links to my writing below, organized into four categories: […]
Elsevier is the world’s largest and most profitable scientific publisher, making a profit of 1.1 billion dollars on revenue of 3.2 billion dollars in 2009. Elsevier have also been involved in many dubious practices, including the publishing of fake medical journals sponsored by pharmaceutical companies, and the publication of what are most kindly described as […]
That’s the question I address (very partially) in a new post on my data-driven intelligence blog. The post reviews some of the recent work on causal inference done by people such as Judea Pearl. In particular the post describes the elements of a causal calculus developed by Pearl, and explains how the calculus can be […]
Click through for event details. I’ve included a few private events at organizations where it’s possible some readers work. The Tech Museum (Bay Area) November 1 Harvard Book Store / Cambridge Forum (Boston) November 9 Authors@Google (Bay Area) November 15. San Francisco Public Library (San Francisco) November 15 Microsoft Colloquium (Seattle) November 16 Town Hall […]
During a recent talk David Weinberger asked me (paraphrasing) whether and how the nature of scientific knowledge will change when it’s produced by large networked collaborations? It’s a great question. Suppose it’s announced in the next few years that the LHC has discovered the Higgs boson. There will, no doubt, be a peer-reviewed scientific paper […]