Today we're releasing episode 15 of DataChats. Here, Hugo interviews Andreas Müller about his work at Columbia University, and as a contributor to scikit-learn. Check it out!
Hi pythonistas! We just released episode 15 of our DataChats video series.
In this episode, Hugo interviews Andreas Müller. Andy is a lecturer at the Data Science Institute at Columbia University and author of the O'Reilly book "Introduction to machine learning with Python", describing a practical approach to machine learning with python and scikit-learn. He is one of the core developers of the scikit-learn machine learning library, and he has been co-maintaining it for several years. He's also a Software Carpentry instructor. In the past, he worked at the NYU Center for Data Science on open source and open science, and as a Machine Learning Scientist at Amazon. His mission is to create open tools to lower the barrier of entry for machine learning applications, promote reproducible science and democratize the access to high-quality machine learning algorithms. You can take his course, Supervised Learning with scikit-learn, here.
Andy answers Hugo's questions about his work at Columbia, gives advice to people starting with data science and answers what the most difficult part of his job is.
We hope that you enjoy watching this series and make sure not to miss any of our upcoming episodes by subscribing to DataCamp's YouTube channel!