A machine learning craftsmanship blog.
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International Conference on Machine Learning.
A delightful machine learning tool that allows you to train/fit, test and use models without writing code.
Illusion Diffusion supports machine learning models, deployment, inspection, datasets, or AI development workflows.
Implementation of image to image (pix2pix) translation from the paper by isola et al.[DEEP LEARNING].
Helps teams build, deploy, observe or operate machine-learning systems.
A toolkit to help understand models and enable responsible machine learning.
IUMB supports machine learning models, deployment, inspection, datasets, or AI development workflows.
Autograd and XLA for high-performance machine learning research.
Notes on what I'm thinking about, learning, and working on.
Machine learning toolkit with classification and clustering for Node.js; supports visualization (see visualml.io).
A JavaScript Native PyTorch-aligned Machine Learning Framework, built from scratch on WebGPU.
An unsupervised machine learning extension library for NetworkX with a Scikit-Learn like API.
Version control for machine learning with support to Amazon S3 and Google Cloud Storage.
Koç University Deep Learning Framework.
Kokoro-82M supports machine learning models, deployment, inspection, datasets, or AI development workflows.
Deep learning framework written in Kotlin.
Machine Learning Toolkit for Kubernetes.
Machine Learning Pipelines for Kubeflow.
LabNotebook is a tool that allows you to flexibly monitor, record, save, and query all your machine learning experiments.
Simple, concise implementations of machine learning techniques and utilities in Clojure.
Energy-based machine learning models built upon PyTorch.
LifeArchitect supports machine learning models, deployment, inspection, datasets, or AI development workflows.
Lightly is a computer vision framework for self-supervised learning.