visenger
I am the queen of ml-ops.org Working at the intersection of software engineering and machine learning. PhD in Augmented Data Quality.
Berlin, Germany
visenger's Stars
ripienaar/free-for-dev
A list of SaaS, PaaS and IaaS offerings that have free tiers of interest to devops and infradev
ageron/handson-ml2
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
ageron/handson-ml
⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 instead.
EthicalML/awesome-production-machine-learning
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
jtoy/awesome-tensorflow
TensorFlow - A curated list of dedicated resources http://tensorflow.org
cortexlabs/cortex
Production infrastructure for machine learning at scale
firmai/industry-machine-learning
A curated list of applied machine learning and data science notebooks and libraries across different industries (by @firmai)
alirezadir/Production-Level-Deep-Learning
A guideline for building practical production-level deep learning systems to be deployed in real world applications.
ligurio/awesome-ci
The list of continuous integration services and tools
awslabs/deequ
Deequ is a library built on top of Apache Spark for defining "unit tests for data", which measure data quality in large datasets.
QData/TextAttack
TextAttack 🐙 is a Python framework for adversarial attacks, data augmentation, and model training in NLP https://textattack.readthedocs.io/en/master/
MarquezProject/marquez
Collect, aggregate, and visualize a data ecosystem's metadata
ddd-crew/context-mapping
davified/clean-code-ml
:bathtub: Clean Code concepts adapted for machine learning and data science. Now a free video series 😎 https://bit.ly/2yGDyqT
hundredblocks/ml-powered-applications
Companion repository for the book Building Machine Learning Powered Applications
devopsbookmarks/devopsbookmarks.com
Website of devopsbookmarks.com
rasbt/stat453-deep-learning-ss20
STAT 453: Intro to Deep Learning @ UW-Madison (Spring 2020)
ckaestne/seai
CMU Lecture: Machine Learning In Production / AI Engineering / Software Engineering for AI-Enabled Systems (SE4AI)
ckaestne/seaibib
Software Engineering for AI/ML -- An Annotated Bibliography
dslp/dslp-repo-template
Template repository for data science lifecycle project
ml-tooling/ml-project-template
ML project template facilitating both research and production phases.
cmawer/reproducible-model
binaryaffairs/a-la-mode
A tool for describing pure data pipelines that enables avoiding repeating work (incrementality) and keeping old data around (provenance)
rest-feeds/rest-feeds
Asynchronous data replication and event streaming with plain REST/HTTP.
jasminevasandani/NLP_Classification_Model_FakeNews
Using NLP and Classification Models to distinguish between fake news and absurd news.
adbreind/open-standard-models-2019
aronchick/MLOps-pipeline
axsaucedo/seldon-core
Machine Learning Deployment for Kubernetes
innoq/ml-ops.org
ML Ops Microsite
visenger/imdb_keras
train and predict imdb sentiment using keras