How To Apply Machine Learning And Deep Learning Methods to Audio Analysis

Written by comet.ml | Published 2019/11/18
Tech Story Tags: datascience | deep-learning | programming | software-engineering | artificial-intelligence | machine-learning | hackernoon-top-story | good-company

TLDR Audio analysis is a growing sub domain of deep learning applications. Comet is a tool for data scientists and AI practitioners to use Comet to apply machine learning and deep learning methods in the domain of audio analysis. To understand how models can extract information from digital audio signals, we’ll dive into some of the core feature engineering methods. We will then use Librosa, a great python library for audio analysis, to code up a short python example training a neural architecture on the UrbanSound8k dataset. To view the code, training visualizations, visit the Comet project page.via the TL;DR App

no story

Written by comet.ml | Allowing data scientists and teams the ability to track, compare, explain, reproduce ML experiments.
Published by HackerNoon on 2019/11/18