Dev tools · alternatives · 2026

24 alternatives to Mljar-Supervised: AutoML Package with Explanations and Markdown Reports

Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation - mljar/mljar-supervised

Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Mljar-Supervised: AutoML Package with Explanations and Markdown Reports launched in 2020; newer entries below may have overtaken it.

1
AutoML Python Package for Tabular Data with Automatic Documentation▲67
Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation - mljar/mljar-supervised
2022 · github.com · its alternatives →
2
Mljar Automated Machine Learning for Tabular Data (Explanation,AutoDoc)▲33
Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation - mljar/mljar-supervised
2021 · github.com · its alternatives →
3
Automated Machine Learning designed to save time for a data scientist▲5
Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation - mljar/mljar-supervised
2020 · github.com · its alternatives →
4
Web App with GUI for AutoML on Tabular Data▲41
AutoML Web App - build Machine Learning pipeline in automatic way with Graphical User Interface (GUI). You can run app locally! - mljar/automl-app
2023 · github.com · its alternatives →
5
SapientML – Generative AutoML for Tabular Data▲82
Generative AutoML for Tabular Data. Contribute to sapientml/sapientml development by creating an account on GitHub.
2023 · github.com · its alternatives →
6
Autolabel, a Python library to label and enrich text data with LLMs▲153
Hi HN! I'm excited to share Autolabel, an open-source Python library to label and enrich text datasets with any Large Language Model (LLM) of your choice. We built Autolabel because access to clean, labeled data is a huge bottleneck for most ML/data science teams. The most capable LLMs are able to label data with high accuracy, and at a fraction of the cost and time compared to manual labeling. With Autolabel, you can leverage LLMs to label any text dataset with <5 lines of code. We’re eager for your feedback!
2023 · github.com · its alternatives →
7
Mljar Studio – local AI data analyst that saves analysis as notebooks▲73
Hi HN, I’ve been working on mljar-supervised (open-source AutoML for tabular data) for a few years. Recently I built a desktop app around it called MLJAR Studio. The idea is simple: you talk to your data in natural language, the AI generates Python code, executes it locally, and the whole conversation becomes a reproducible notebook (*.ipynb file). So instead of just chatting with data, you end up with something you can inspect, modify, and rerun. What MLJAR Studio does: - Sets up a local Python environment automatically, runs on Mac, Windows, and Linux - Installs missing packages during the…
May 2026 · mljar.com · its alternatives →
8
StackML▲252
Machine Learning platform in-browser, for creators
2019 · its alternatives →
9
Igel – A CLI tool to run machine learning without writing code▲405
a delightful machine learning tool that allows you to train, test, and use models without writing code - nidhaloff/igel
2020 · github.com · its alternatives →
10
ScoopML▲81
An AI assistant for machine learning engineers
2020 · its alternatives →
11
Python package and CLI to generate stylistic word clouds▲112
Python package + CLI to generate stylistic wordclouds, including gradients and icon shapes! - minimaxir/stylecloud
2019 · github.com · its alternatives →
12
Provide a CSV and a target field, generate a model and code to run it▲172
Provide an input CSV and a target field to predict, generate a model + code to run it. - minimaxir/automl-gs
2019 · github.com · its alternatives →
13
automl-docker▲68
Open-source, easily create ready-to-use ML models for NLP
2022 · github.com · its alternatives →
14
NannyML Regression v0.8.0▲85
OSS Python library for detecting silent ML model failure
2022 · nannyml.com · its alternatives →
15AL
A labelling tool to easily extract and label Wikipedia data▲116
Hi HN! I am Maria, solo founder of DataQA (https://dataqa.ai/), a tool to search and label documents for various NLP tasks (e.g. entity extraction, entity linking, etc). I have worked as a data scientist and ML engineer for the better part of a decade, and over that time have specialised mainly in applications involving natural language processing (NLP). One of the key questions I have always had at the back of my mind is whether my time was well spent. Whenever I spent more time on feature engineering or trying different models, I always wondered whether I would get better…
2021 · its alternatives →
16
A design-by-contract Python package in ~100 lines▲58
Greetings! A 2.5 weekends project to teach myself newer Python features (>= 3.10). Conditions are written as Lambda expressions that annotate parameters and return types, and coexist with type annotations. Symbols to share values between conditions are also supported to a limited extend.
2022 · github.com · its alternatives →
17
Lance – Alternative to Parquet for ML data▲85
Open Lakehouse Format for Multimodal AI. Convert from Parquet in 2 lines of code for 100x faster random access, vector index, and data versioning. Compatible with Pandas, DuckDB, Polars, Pyarrow, and PyTorch with more integrations coming.. - lance-format/lance
2023 · github.com · its alternatives →
18
An annotation tool for ML and NLP▲76
The easy way to turn text into structure data
2021 · getmarkup.com · its alternatives →
19
Machine learning automation from creating to using models in production▲72
a delightful machine learning tool that allows you to train, test, and use models without writing code - GitHub - nidhaloff/igel at v0.4.0
2021 · github.com · its alternatives →
20
ZenML▲84
Create reproducible machine learning pipelines
2020 · github.com · its alternatives →
21
Hyperparam: OSS tools for exploring datasets locally in the browser▲77
For the last year I’ve been developing Hyperparam — a collection of small, fast, dependency-free open-source libraries designed for data scientists and ML engineers to actually look at their data. - Hyparquet: Read any Parquet file in browser/node.js - Icebird: Explore Iceberg tables without needing Spark/Presto - HighTable: Virtual scrolling of millions of rows - Hyparquet-Writer: Export Parquet easily from JS - Hyllama: Read llama.cpp .gguf LLM metadata efficiently CLI for viewing local files: npx hyperparam dataset.parquet Example dataset on Hugging Face Space:…
2025 · hyperparam.app · its alternatives →
22
ZenML, extensible open-source MLOps framework for reproducible ML▲37
ZenML 🙏: One AI Platform from Pipelines to Agents. https://zenml.io. - zenml-io/zenml
2020 · github.com · its alternatives →
23
Hyperactive – A highly versatile AutoML Toolbox▲7
A unified interface for optimization algorithms and experiments - hyperactive-project/Hyperactive
2021 · github.com · its alternatives →
24
Łukasiewicz - Tabular data to ML model▲15
Get a Machine Learning model for your data with single click
2024 · its alternatives →

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Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →