Dev tools · alternatives · 2026
24 alternatives to SapientML – Generative AutoML for Tabular Data
Generative AutoML for Tabular Data. Contribute to sapientml/sapientml development by creating an account on GitHub.
SapientML is an automated machine learning tool designed for tabular data analysis. It generates machine learning pipelines automatically, reducing the need for manual model building and feature engineering. The tool… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Prices are shown for the 1 we have checked on their own sites, 1 of them free or with a free tier. SapientML – Generative AutoML for Tabular Data launched in 2023; newer entries below may have overtaken it.
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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 →
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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 →
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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 →
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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 →
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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 →
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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 →
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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 →
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Built a tool for transforming unstructured data into structured outputs using language models (with 100% adherence). If you're facing problems getting GPT to adhere to a schema (JSON, XML, etc.) or regex, need to bulk process some unstructured data, or generate synthetic data, check it out. We run our own tuned model (you can self-host if you want), so, we're able to have incredibly fine grained control over text generation. Repository: https://github.com/automorphic-ai/trex Playground: https://automorphic.ai/playground
2023 · automorphic.ai · its alternatives →
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Create interactive data tables in seconds with Tabulator. A free, open source, fully featured JavaScript table / data grid generation library.
2018 · tabulator.info · its alternatives →
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Get a Machine Learning model for your data with single click
2024 · its alternatives →
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The fastest, most precise no-code AI in the world.
2020 · obviously.ai · its alternatives →
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Sambot▲69AutoML assistant that does some predictions automatically
2022 · chromewebstore.google.com · its alternatives →
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Train custom ML models with minimum effort and expertise
2018 · cloud.google.com · its alternatives →
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Dynamic AutoML: Automate Data Tasks for Smarter Results.
2024 · github.com · its alternatives →
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Open-source, easily create ready-to-use ML models for NLP
2022 · github.com · its alternatives →
- 20DS
2019 · dbml-lang.org · its alternatives →
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Creating data visualizations with AI nowadays often means chat, chat and more chats...and writing long prompts can be annoying while they are also not the most effective way to describe your visualization designs. Data Formulator blends UI interaction with natural language so that you can create visualizations with AI much more effectively! You can: * create rich visualizations beyond initial datasets, where AI helps transforming and visualizing data along the way * iterate your designs and dive deeper using data threads, a new way to manage your conversation with AI. Here is a demo video:…
2024 · github.com · its alternatives →
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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 →
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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 →
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CRML▲130CRML is a declaritive language for writing cyberrisk as code
Feb 2026 · github.com · its alternatives →
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- Mljar-Supervised: AutoML Package with Explanations and Markdown Reports alternatives
- Provide a CSV and a target field, generate a model and code to run it alternatives
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 →