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Librosa: Audio and Music Processing in Python with Brian McFee - TWiML Talk #263

Librosa: Audio and Music Processing in Python with Brian McFee - TWiML Talk #263

FromThe TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)


Librosa: Audio and Music Processing in Python with Brian McFee - TWiML Talk #263

FromThe TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)

ratings:
Length:
38 minutes
Released:
May 9, 2019
Format:
Podcast episode

Description

Today we continue our PyDataSci series joined by Brian McFee, assistant professor of music technology and data science at NYU, and creator of LibROSA, a python package for music and audio analysis. Brian walks us through his experience building LibROSA, including: • Detailing the core functions provided in the library, • His experience working within Jupyter Notebook, • We explore a typical LibROSA workflow & more! The complete show notes for this episode can be found at twimlai.com/talk/263. Check out the rest of the PyDataSci series at twimlai.com/pydatasci. We want to better understand your views on the importance of open source and the projects and players in this space. To access the survey visit twimlai.com/pythonsurvey. Thanks to this weeks sponsor, IBM, for their support of the podcast! Visit twimlai.com/ibm to learn more about the IBM Data Science Community.
Released:
May 9, 2019
Format:
Podcast episode

Titles in the series (100)

This Week in Machine Learning & AI is the most popular podcast of its kind. TWiML & AI caters to a highly-targeted audience of machine learning & AI enthusiasts. They are data scientists, developers, founders, CTOs, engineers, architects, IT & product leaders, as well as tech-savvy business leaders. These creators, builders, makers and influencers value TWiML as an authentic, trusted and insightful guide to all that’s interesting and important in the world of machine learning and AI. Technologies covered include: machine learning, artificial intelligence, deep learning, natural language processing, neural networks, analytics, deep learning and more.