The Best DVC Alternatives in 2026

oneDAL is a C++ and DPC++ library for accelerated machine learning routines on tabular data, governed by the UXL Foundation.

Cleanlab provides a Python library for data quality and machine learning with messy real world data and labels.

Lance provides an open lakehouse format for multimodal AI, with vector indexing and data versioning.

DVCLive logs and tracks machine learning metrics, parameters, and models with Git or DVC.

19 Questions assigns attributes to objects using machine learning and Bayesian inference, according to its project description.

Feature Engine provides Python tools for feature engineering and selection that are compatible with scikit-learn.

mljar-supervised provides tabular data AutoML with feature engineering, hyperparameter tuning, explanations, and documentation.

tsfresh automatically extracts relevant features from time series data.

Snorkel helps generate training data programmatically through weak supervision.

This project profiles data quality and supports exploratory analysis of Pandas and Spark DataFrames.

The Featuretools Python library supports automated feature engineering and is published as open source.

Python library for decision tree visualization and model interpretation.

PyCaret provides a low code AutoML platform for Python, with a scikit-learn native engine and React control plane.

Optimus supports agile data preparation workflows across Pandas, Dask, cuDF, Vaex, and PySpark.

DrivenData hosts data science competitions where participants build predictive models for organizations addressing social challenges.

Ultralytics supports detection, segmentation, image classification, pose estimation, and tracking across YOLO model versions.

A tool to help you configure, organize, log and reproduce experiments.

InterpretML fits interpretable models and explains results from black-box machine learning systems.

The LightGBM framework uses gradient boosting for ranking, classification, and other machine learning tasks.

nilearn provides Python tools for machine learning and neuroimaging analysis.

A Python package to assess and improve fairness of machine learning models.

Manifold provides visual debugging for machine learning models without depending on a specific model type.

This Swift library builds machine learning predictions using linear regression.

Python package which helps to debug machine learning classifiers and explain their predictions.