SkafteNicki

dtu_mlops

Exercises and supplementary material for the machine learning operations course at DTU.

pl_crossvalidate

libcpab

CPAB Transformations: finite-dimensional spaces of simple, fast, and highly-expressive diffeomorphisms derived from parametric, continuously-defined, velocity fields in Numpy, Tensorflow and Pytorch

mlops_template

ku_devops

john

py_uci

Python library for loading data from the UCI Machine Learning Repository

pytorch-metrics

Metrics for pytorch

example_mlops

pytorch-lightning

The lightweight PyTorch wrapper for ML researchers. Scale your models. Write less boilerplate

pytorchtape

SkafteNicki.github.io

My Github pages personal webpage

calibrated_vae

cusolver_example

Example of calling cusolver from python by using pytorch

best_devops

cookiecutter-data-science

A logical, reasonably standardized, but flexible project structure for doing and sharing data science work.

deep-learning-v2-pytorch

Projects and exercises for the latest Deep Learning ND program https://www.udacity.com/course/deep-learning-nanodegree--nd101

delira

Lightweight framework for fast prototyping and training deep neural networks with PyTorch and TensorFlow

evidently

Evidently is ​​an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.

gcp_docker_example

gcp_monitoring_test

gh_tester

gha_dvc_test

hvae-oodd

Official source code repository for the ICML 2021 paper "Hierarchical VAEs Know What They Don't Know"

ignite

High-level library to help with training and evaluating neural networks in PyTorch flexibly and transparently.

just-the-docs

A modern, high customizable, responsive Jekyll theme for documention with built-in search.

minimal-mistakes

:triangular_ruler: Jekyll theme for building a personal site, blog, project documentation, or portfolio.

scikit-learn

scikit-learn: machine learning in Python

tape

Tasks Assessing Protein Embeddings (TAPE), a set of five biologically relevant semi-supervised learning tasks spread across different domains of protein biology.

tape-1

Tasks Assessing Protein Embeddings (TAPE), a set of five biologically relevant semi-supervised learning tasks spread across different domains of protein biology.