mllint VS MLOps

Compare mllint vs MLOps and see what are their differences.

mllint

`mllint` is a command-line utility to evaluate the technical quality of Python Machine Learning (ML) projects by means of static analysis of the project's repository. (by bvobart)
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mllint MLOps
3 2
72 1,716
- 6.3%
3.8 2.5
almost 2 years ago 9 months ago
Go Jupyter Notebook
GNU General Public License v3.0 only MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

mllint

Posts with mentions or reviews of mllint. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-09-16.

MLOps

Posts with mentions or reviews of MLOps. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-09-16.

What are some alternatives?

When comparing mllint and MLOps you can also consider the following projects:

mlnotify - 🔔 No need to keep checking your training - just one import line and you'll know the second it's done.

MLflow - Open source platform for the machine learning lifecycle

CortexTheseus - Cortex - AI on Blockchain, Official Golang implementation

dvc - 🦉 ML Experiments and Data Management with Git

spaCy - 💫 Industrial-strength Natural Language Processing (NLP) in Python

mlops-with-vertex-ai - An end-to-end example of MLOps on Google Cloud using TensorFlow, TFX, and Vertex AI

gorse - Gorse open source recommender system engine

pytorch-deepdream - PyTorch implementation of DeepDream algorithm (Mordvintsev et al.). Additionally I've included playground.py to help you better understand basic concepts behind the algo.

awesome-seml - A curated list of articles that cover the software engineering best practices for building machine learning applications.

dslinter - `dslinter` is a pylint plugin for linting data science and machine learning code. We plan to support the following Python libraries: TensorFlow, PyTorch, Scikit-Learn, Pandas and NumPy.

MachineLearningNotebooks - Python notebooks with ML and deep learning examples with Azure Machine Learning Python SDK | Microsoft