Providing reproducibility in deep learning frameworks
- Updated
May 13, 2024 - Python
Providing reproducibility in deep learning frameworks
Pitch-shift audio clips quickly with PyTorch (CUDA supported)! Additional utilities for searching efficient transformations are included.
Python Suite for Advanced General Ensemble Simulations
Time-stretch audio clips quickly with PyTorch (CUDA supported)! Additional utilities for searching efficient transformations are included.
"A neural network to rule them all, a neural network to find them, a neural network to bring them all and verify if is you !!" (Face recognition tool)
Fast CPU and GPU Python implementations of Improved Kernel Partial Least Squares (PLS) by Dayal and MacGregor (1997) and Fast Partition-Based Cross-Validation With Centering and Scaling for XTX and XTY by Engstrøm and Jensen (2025).
This is a sandbox manager developed using Django, providing isolated development environments with a suite of base functions and packages for each user on the same machine by using Docker.
Real-time object detection system utilizing the SSD MobileNet V2 FPNLite 320x320 model for high-speed, efficient recognition.
Re-Implementation of Google Research's VGGish model used for extracting audio features using Pytorch with GPU support.
Simplify GPU Setup: Drivers, CUDA, Frameworks, and more!
An Ansible role to deploy a docker environment on specific linux systems (with some extras like ctop, docker-compose, GPU support in docker for Nvidia graphic cards)
Simple application for digit recognition with CNN using four different datasets
An automated pipeline for GPU-based ML training using AWS EC2 Spot Instances
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