Name: Scott H. Hawley
Type: User
Company: Belmont University, Physics
Bio: Physics prof, musician, code tinkerer. Specialty: ML + Musical Audio
Twitter: drscotthawley
Location: Nashville, TN
Blog: http://hedges.belmont.edu/~shawley/
Scott H. Hawley's Projects
🚀 A simple way to train and use PyTorch models with multi-GPU, TPU, mixed-precision
Swift: Example of a popover window with a navigation controller and multiple pages for user selection
(ML) audio engineering i/o utils
audio engineering i/o utilities
Hawley's fork for Hooper's A.I. class: Python implementation of algorithms from Russell And Norvig's "Artificial Intelligence - A Modern Approach"
All-In-One Music Structure Analyzer
Renders papers from Arxiv as responsive web pages so you don't have to squint at a PDF.
alchemy with embeddings
Audio Classifier in Keras using Convolutional Neural Network
zach's audio-diffusion work. check various branches (not main!)
Extract the melody from an audio file and export to MIDI
Audiocraft is a library for audio processing and generation with deep learning. It features the state-of-the-art EnCodec audio compressor / tokenizer, along with MusicGen, a simple and controllable music generation LM with textual and melodic conditioning.
Object-oriented handling of audio data, with GPU-powered augmentations, and more.
EFA/NCCL base AMI build Packer and CodeBuild/Pipeline files. Also base Docker build files to enable EFA/NCCL in containers
A lightweight yet powerful audio-to-MIDI converter with pitch bend detection
my new blog site
Scott H. Hawley's Blog
Quarto version of former fastpages blog
An autograder for jupyter notebooks
Silicon Valley Hacks hackathon winner
Command-line client for Canvas by Instructure
Contrastive Language-Audio Pretraining
The 3rd edition of course.fast.ai - coming in 2019
My CV built using RMarkdown and the pagedown package.
A minimal example of nbdev using code from Allen Downey's Think Python 2nd Ed
# Deep Learning with Keras
DeepAFx-ST - Style transfer of audio effects with differentiable signal processing. Please see https://csteinmetz1.github.io/DeepAFx-ST/
Implementation of Denoising Diffusion Probabilistic Model in Pytorch