Dev tools · alternatives · 2026
24 alternatives to Provide a CSV and a target field, generate a model and code to run it
Provide an input CSV and a target field to predict, generate a model + code to run it. - minimaxir/automl-gs
Provide is a developer tool that generates machine learning models and executable code from CSV files by specifying a target field. Users upload their data and designate which column to predict, and 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. Provide a CSV and a target field, generate a model and code to run it launched in 2019; newer entries below may have overtaken it.
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A robust Python tool for text-based AI training and generation using GPT-2. - minimaxir/aitextgen
2020 · github.com · its alternatives →
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Generate keywords with AI in seconds
2023 · adsby.co · its alternatives →
- 3
a delightful machine learning tool that allows you to train, test, and use models without writing code - nidhaloff/igel
2020 · github.com · its alternatives →
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Generative AutoML for Tabular Data. Contribute to sapientml/sapientml development by creating an account on GitHub.
2023 · github.com · its alternatives →
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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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Superusers are intelligent, programmable bots that turn chat into a game you play together. They provide support 24/7, generate music and images, and search the web.
2020 · autocode.com · its alternatives →
- 8UA
Hello! So, I am experimenting with new approaches to automated machine learning, where you don't need anything besides either data or prompt This is a first platform from my auto ml serie called Łukasiewicz (Jan Łukasiewicz was a logician who created Polish notation) I much appreciate your feedback and if you want to try it out, I created a -75% off promo code "HACKERNEWS" on credits, so it hopefully will cover at least some of computing expenses, but more importantly will let you play with the platform at almost no cost Thank you!
2024 · lukasiewicz.tmlc.pl · its alternatives →
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Fast and efficient models optimized for coding and subagents
Mar 2026 · openai.com · its alternatives →
- 10
Train custom ML models with minimum effort and expertise
2018 · cloud.google.com · its alternatives →
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- 12SM
2021 · spotml.io · its alternatives →
- 13
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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Sambot▲69AutoML assistant that does some predictions automatically
2022 · chromewebstore.google.com · its alternatives →
- 15
A web-based application for quick, scalable, and automated hyperparameter tuning and stacked ensembling in Python. - reiinakano/xcessiv
2017 · github.com · its alternatives →
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Python package + CLI to generate stylistic wordclouds, including gradients and icon shapes! - minimaxir/stylecloud
2019 · 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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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 →
- 19
built a tiny pytorch clone in c after going through prof. vijay janapa reddi's mlsys book: mlsysbook.ai/tinytorch/ perfect for learning how ml frameworks work under the hood :)
Dec 2025 · github.com · its alternatives →
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- Discovering the most effective RAG pipeline for your specific data and use case can be daunting. It requires experimenting with various RAG modules and configurations, which are both time-consuming and complex. - AutoRAG addresses this challenge by automatically evaluating different combinations of RAG modules and their parameters. You don't need to write implementation code yourself; everything is set up through a single YAML file. - Our aim is to save you the hassle of continuously adapting to new RAG modules and configurations. Instead, you can focus on developing robust data for your…
2024 · github.com · its alternatives →
- 21FB
My friends and I were complaining about having to decipher incomprehensible code one day and decided to pass the code through GPT to see if it could write easily understandable comments to help us out. It turns out that GPT can but it was still a hassle to generate comments for large files. So we decided to develop a basic web application that automatically integrates with your Github repository, generate comments, create a pull request and send you an email when it is all done. There is definitely a lot more that can be done but we wanted to gain feedback on whether this is a problem that…
2023 · swiftstart.vercel.app · its alternatives →
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Convert your vector embeddings into a set of questions and their ideal responses. Use this dataset to test your LLM and catch failures caused by prompt or RAG updates. Get started in 3 lines of code: ``` pip3 install fiddlecube ``` ``` from fiddlecube import FiddleCube fc = FiddleCube(api_key="") dataset = fc.generate( [ "The cat did not want to be petted.", "The cat was not happy with the owner's behavior.", ], 10, ) dataset ``` Generate your API key: https://dashboard.fiddlecube.ai/api-key # Ideal QnA datasets for testing, eval and training LLMs Testing, evaluation or…
2024 · github.com · its alternatives →
- 23
I built CSV GB+ by Data.olllo, a local data tool that lets you open, clean, and export gigabyte-sized CSVs (even billions of rows) without writing code. Most spreadsheet apps choke on big files. Coding in pandas or Polars works—but not everyone wants to write scripts just to filter or merge CSVs. CSV GB+ gives you a fast, point-and-click interface built on dual backends (memory-optimized or disk-backed) so you can process huge datasets offline. Key Features: Handles massive CSVs with ease — merge, split, dedup, filter, batch export Smart engine switch: disk-based "V Core" or RAM-based "P…
2025 · apps.microsoft.com · its alternatives →
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VSCode extension to generate comments for code snippets.
2021 · marketplace.visualstudio.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 →