| apache/airflow |
33,219 |
|
0 |
320 |
about 2 years ago |
169 |
November 27, 2023 |
890 |
apache-2.0 |
Python |
| Apache Airflow - A platform to programmatically author, schedule, and monitor workflows |
| jina-ai/jina |
19,573 |
|
0 |
16 |
about 2 years ago |
2,453 |
December 01, 2023 |
19 |
apache-2.0 |
Python |
| ☁️ Build multimodal AI applications with cloud-native stack |
| argoproj/argo-workflows |
13,966 |
|
24 |
51 |
about 2 years ago |
449 |
November 27, 2023 |
993 |
apache-2.0 |
Go |
| Workflow Engine for Kubernetes |
| kubeflow/kubeflow |
13,364 |
|
0 |
3 |
about 2 years ago |
64 |
November 01, 2023 |
397 |
apache-2.0 |
TypeScript |
| Machine Learning Toolkit for Kubernetes |
| kedro-org/kedro |
10,770 |
|
8 |
64 |
about 2 months ago |
46 |
October 18, 2023 |
273 |
apache-2.0 |
Python |
| Kedro is a toolbox for production-ready data science. It uses software engineering best practices to help you create data engineering and data science pipelines that are reproducible, maintainable, and modular. |
| stanfordnlp/stanza |
6,931 |
|
2 |
91 |
about 2 years ago |
22 |
December 03, 2023 |
83 |
other |
Python |
| Stanford NLP Python library for tokenization, sentence segmentation, NER, and parsing of many human languages |
| mage-ai/mage-ai |
6,324 |
|
0 |
0 |
about 2 years ago |
314 |
December 06, 2023 |
189 |
apache-2.0 |
Python |
| 🧙 The modern replacement for Airflow. Build, run, and manage data pipelines for integrating and transforming data. |
| allegroai/clearml |
5,009 |
|
0 |
16 |
about 2 years ago |
143 |
November 08, 2023 |
426 |
apache-2.0 |
Python |
| ClearML - Auto-Magical CI/CD to streamline your ML workflow. Experiment Manager, MLOps and Data-Management |
| Spandan-Madan/DeepLearningProject |
4,043 |
|
0 |
0 |
over 5 years ago |
0 |
|
3 |
mit |
HTML |
| An in-depth machine learning tutorial introducing readers to a whole machine learning pipeline from scratch. |
| alirezadir/Production-Level-Deep-Learning |
3,957 |
|
0 |
0 |
over 2 years ago |
0 |
|
7 |
|
|
| A guideline for building practical production-level deep learning systems to be deployed in real world applications. |
