neptune-contrib VS MLflow

Compare neptune-contrib vs MLflow and see what are their differences.

Our great sponsors
  • Scout APM - Truly a developer’s best friend
  • talent.io - Download talent.io’s Tech Salary Report
  • SonarQube - Static code analysis for 29 languages.
neptune-contrib MLflow
0 33
26 12,667
- 2.4%
1.0 9.9
12 months ago 2 days ago
Python Python
MIT License Apache License 2.0
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.

neptune-contrib

Posts with mentions or reviews of neptune-contrib. We have used some of these posts to build our list of alternatives and similar projects.

We haven't tracked posts mentioning neptune-contrib yet.
Tracking mentions began in Dec 2020.

MLflow

Posts with mentions or reviews of MLflow. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-09-25.

What are some alternatives?

When comparing neptune-contrib and MLflow you can also consider the following projects:

clearml - ClearML - Auto-Magical CI/CD to streamline your ML workflow. Experiment Manager, MLOps and Data-Management

Sacred - Sacred is a tool to help you configure, organize, log and reproduce experiments developed at IDSIA.

zenml - ZenML 🙏: Build portable, production-ready MLOps pipelines. https://zenml.io.

dvc - 🦉Data Version Control | Git for Data & Models | ML Experiments Management

guildai - Experiment tracking, ML developer tools

tensorflow - An Open Source Machine Learning Framework for Everyone

neptune-client - :ledger: Experiment tracking tool and model registry

Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.

H2O - H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

gensim - Topic Modelling for Humans

Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows

onnxruntime - ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator