Machines Learning about Humans Learning about Machines Learning
I had the great honor and pleasure of presenting the first tutorial at AnacondaCon 2018, on machine learning with scikit-learn. I spoke to a full room of…
Deploying Machine Learning Models is Hard, But It Doesn’t Have to Be
With free, open source tools like Anaconda Distribution, it has never been easier for individual data scientists to analyze data and build machine learn…
Anaconda Distribution 5.2 Released
We’re excited to announce the release of Anaconda Distribution 5.2! With over 6 million users, Anaconda Distribution is the world’s most popu…
CyberPandas: Extending Pandas with Richer Types
Over the past couple months, Anaconda has supported a major internal refactoring of pandas. The outcome is a new extension array interface that will enab…
March 2018 Kubernetes Security Vulnerabilities and Anaconda Enterprise
The Anaconda team tracks security vulnerabilities and CVEs via the National Vulnerability Database (NVD) on an ongoing basis. Our team is committed to th…
Anaconda Repository Changes Afoot
In August 2017, Continuum Analytics announced it is now Anaconda, Inc. Here at Anaconda, we are all excited about the change, and have spent the last sev…
The Case for Numba in Community Code
The numeric Python community should consider adopting Numba more widely within community code. Numba is strong in performance and usability, but historically weak in ease of installation and community trust. This blog post discusses these strengths and weaknesses from the perspective of an OSS library maintainer. It uses other more technical blog posts written on […]
Introducing Anaconda Enterprise 5
From its inception, Anaconda has had the mission to build better products for data scientists and the organizations they serve. We were the first company…
Anaconda to Present at Strata Data Conference, New York
Presentation topics include scaling Python workloads; solving problems faced by enterprise data science teams; exploring the architecture and current app…
Parallel Python with Numba and ParallelAccelerator
With CPU core counts on the rise, Python developers and data scientists often struggle to take advantage of all of the computing power available to them….
