A workshop on installing python with conda and using multiple environments for isolation and reproducibility

When and Where?

11AM EST, 9.30 PM IST, Thursday Mar 03rd, 2022  Register

Details and Outcomes

Many python libraries do not work well together. For example it is hard to install tensorflow and pytorch together. Pre-requisites clash, and you land up with a not working python interpreter.

The solution to this is to create isolatable python environments, with files that specify what packages should be installed, so that we can reproduce our environments. And then make these environments available to our applications, specifically Jupyterlab.

This workshop will make you an old hand and easily booting up isolated python projects for your data science work.


Dr. Rahul Dave

Rahul is co-founder of Univ.AI. He was previously a lecturer at Harvard University. He was on the original team for Harvard’s famous Data Science course, cs109, and has taught machine learning, statistics, and AI courses, both at Harvard and at multiple conferences and workshops. Some of his more popular offerings have been the Data Scientist Training for Librarians workshops in Boston and Copenhagen, Machine Learning for Suits at the Open Data Science Conference, continuing versions of cs109, and the am207 course on Bayesian Statistics and Generative Models at Harvard. Rahul is an accomplished computational scientist with a strong programming background and a veteran cosmologist. His Ph.D. thesis in cosmology and astrophysics at the University of Pennsylvania involved both high performance computing and bayesian statistics, and was one of the first works introducing dark energy. His subsequent work in Solar System astronomy and large scale astronomy databases at the ADS took him in the direction of machine learning and AI. Rahul is passionate about teaching, and a big believer in exposing big, ‘researchy’ ideas early on, to students. Follow him at @rahuldave on Twitter.