AI · alternatives · 2026

24 alternatives to Web App with GUI for AutoML on Tabular Data

AutoML Web App - build Machine Learning pipeline in automatic way with Graphical User Interface (GUI). You can run app locally! - mljar/automl-app

This is a web application with a graphical interface designed to automate machine learning workflows for tabular data. It enables users to build and train models without extensive coding knowledge. The tool is built… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Web App with GUI for AutoML on Tabular Data launched in 2023; 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
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 →
4
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 →
5
StackML▲252
Machine Learning platform in-browser, for creators
2019 · its alternatives →
6
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 →
7
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 →
8
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 →
9
Mljar-Supervised: AutoML Package with Explanations and Markdown Reports▲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 →
10
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 →
11
Obviously AI AutoML▲276
The fastest, most precise no-code AI in the world.
2020 · obviously.ai · its alternatives →
12
panda{·}etl▲680
Automate your document workflows
2024 · panda-etl.ai · its alternatives →
13
MakeML▲274
Train Neural Networks without a line of code
2019 · makeml.app · its alternatives →
14
ZenML▲84
Create reproducible machine learning pipelines
2020 · github.com · its alternatives →
15
MonkeyLearn 3.0▲363
Get actionable data from text with machine learning
2018 · medallia.com · its alternatives →
16
Automa▲605
Build AI agents and RPA workflows in minutes
2021 · goautoma.com · its alternatives →
17
automl-docker▲68
Open-source, easily create ready-to-use ML models for NLP
2022 · github.com · its alternatives →
18
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 →
19
Continuous Machine Learning – CI/CD for Machine Learning Projects▲171
Bring DevOps practices to your projects for automatic, reproducible, and fast machine learning.
2020 · cml.dev · its alternatives →
20
Google CLOUD AUTOML▲93
Train custom ML models with minimum effort and expertise
2018 · cloud.google.com · its alternatives →
21
ScoopML▲81
An AI assistant for machine learning engineers
2020 · its alternatives →
22
Pocket AutoML▲84
Experiment with a deep learning model right on your device
2021 · play.google.com · its alternatives →
23
Sambot▲69
AutoML assistant that does some predictions automatically
2022 · chromewebstore.google.com · its alternatives →
24
MLConsole – web app to train ML models, for free and client-side▲86
ML Console is a free tool to build an AI model without writing a single line of code. Simply pick a column to predict, and let us handle the rest.
2021 · mlconsole.com · 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 →