DVC
dvc.orgOpen-source version control system for Data Science and Machine Learning projects. Git-like experience to organize your data, models, and experiments.
Looking for something like Bodywork? Here are 24 alternatives, ranked by how closely they match it on purpose, features and platforms. Of these, 17 are open source.
Bodywork deploys machine learning pipelines to Kubernetes and handles containers and orchestration.
| # | Alternative | Pricing | Open source | Platforms |
|---|---|---|---|---|
| 1 | DVC | — | Not stated | Web |
| 2 | Parris | — | Not stated | Linux, Windows |
| 3 | climin | — | Yes | — |
| 4 | Rockpool | — | Yes | — |
| 5 | PyTorchNet | — | Not stated | — |
| 6 | torchvision | — | Yes | — |
| 7 | Kubeflow | — | Yes | — |
| 8 | Cog | — | Yes | — |
| 9 | Feature Stores for ML | — | Not stated | Web |
| 10 | ClearML | — | Yes | — |
Open-source version control system for Data Science and Machine Learning projects. Git-like experience to organize your data, models, and experiments.
Parris, the automated infrastructure setup tool for machine learning algorithms.
The climin package provides optimization methods focused on machine learning scenarios in Python.
Rockpool supports training spiking neural networks with PyTorch and JAX and deploying them to neuromorphic hardware.
PyTorch TNT supplies lightweight tools and utilities for training with PyTorch.
Torchvision provides datasets, transforms, and models for computer vision with PyTorch.
Kubeflow provides a machine learning toolkit for deploying workflows on Kubernetes.
Cog packages machine learning models into containers to support deployment across environments.
Feature Stores for ML shares information and knowledge about feature stores and their role in machine learning pipelines.
ClearML combines experiment and data management, pipelines, scheduling, orchestration, and model serving for AI workloads.
ClearML manages AI experiments, data, pipelines, orchestration, scheduling, and model serving in one MLOps platform.
Merlin supports machine learning model management, deployment, and serving in Kubernetes environments.
Cortex provides cloud infrastructure for deploying, managing, and scaling machine learning models in production.
Replicate provides a cloud API for running and fine-tuning open machine learning models and deploying custom models.
Kubeflow Pipelines orchestrates and manages machine learning workflows on Kubeflow.
TPOT uses genetic programming to optimize machine learning pipelines in Python.
Evidently evaluates, tests, and monitors machine learning systems and data pipelines.
MLRun provides an open-source MLOps platform for managing machine learning applications, pipelines, and CI/CD delivery.
Mosec serves machine learning models with dynamic batching and CPU or GPU pipelines for inference workloads.
Kedro-Viz visualizes Kedro data and machine learning pipelines and tracks experiments.
ZenML provides a platform for machine learning pipelines and AI agents.
MLOps framework to package, deploy, monitor and manage thousands of production machine learning models.
Curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning.
Kale simplifies data science workflows for deploying Kubeflow Pipelines.
Alternatives are suggested from the purpose and features described in our listings. Different pages for the same product appear once. Read each description to check whether it fits your task. How we choose alternatives · Suggest an alternative