--- title: "automl-gs vs FastDatasets" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/minimaxir-automl-gs-vs-zhulinsen-fastdatasets" tools: ["minimaxir-automl-gs", "zhulinsen-fastdatasets"] --- # automl-gs vs FastDatasets *GraphCanon updated Aug 7, 2026* ## Verdict Pick automl-gs if automl-gs: Python tool for automated machine-learning model creation from CSV data; pick FastDatasets if fastDatasets is designed to aid in generating high-quality datasets for training Large Language Models (LLMs), leveraging Python capabilities. [automl-gs](https://github.com/minimaxir/automl-gs) reports 1.9k GitHub stars, 181 forks, and 28 open issues, last pushed Oct 22, 2019. [FastDatasets](https://github.com/ZhuLinsen/FastDatasets) has 222 stars, 43 forks, and 0 open issues, last pushed Aug 31, 2025. Figures are from public GitHub metadata via [automl-gs's repository](https://github.com/minimaxir/automl-gs) and [FastDatasets's repository](https://github.com/ZhuLinsen/FastDatasets). | | [automl-gs](/tools/minimaxir-automl-gs.md) | [FastDatasets](/tools/zhulinsen-fastdatasets.md) | | --- | --- | --- | | Tagline | Automatically generate machine-learning models and code with input CSV and target field | A powerful tool for creating high-quality training datasets for Large Language Models (LLMs) | | Stars | 1,869 | 222 | | Forks | 181 | 43 | | Open issues | 28 | 0 | | Language | Python | Python | | Adopt for | automl-gs: Python tool for automated machine-learning model creation from CSV data | FastDatasets is designed to aid in generating high-quality datasets for training Large Language Models (LLMs), leveraging Python capabilities. | | Persona | - | - | | Runtime | - | - | | License | MIT | Apache-2.0 | | Categories | Data & Retrieval, Model Training | Data & Retrieval, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [automl-gs](/tools/minimaxir-automl-gs.md) | [FastDatasets](/tools/zhulinsen-fastdatasets.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Slowing (36%) | | Days since push | 2477d | 340d | | Open issues (now) | 28 | 0 | | Full report | [trust report](/tools/minimaxir-automl-gs/trust.md) | [trust report](/tools/zhulinsen-fastdatasets/trust.md) | ## Decision facts: automl-gs - **Adopt for:** automl-gs: Python tool for automated machine-learning model creation from CSV data ## Decision facts: FastDatasets - **Adopt for:** FastDatasets is designed to aid in generating high-quality datasets for training Large Language Models (LLMs), leveraging Python capabilities. ## Choose when ### Choose automl-gs if… - License: automl-gs is MIT, FastDatasets is Apache-2.0. - Tags unique to automl-gs: automl, keras, machine-learning, tensorflow. - Need to rapidly prototype models with limited ML expertise ### Choose FastDatasets if… - License: FastDatasets is Apache-2.0, automl-gs is MIT. - Tags unique to FastDatasets: asyncio, dataset-generation, datasets, llm. - - When you need to generate datasets specifically tailored to improve the performance of LLMs. ## When NOT to use automl-gs - Complex feature engineering or non-standard data inputs required - Sensitive about licensing of the generated code ## When NOT to use FastDatasets - - Avoid using if the project does not involve training or fine-tuning LLMs as its primary objective. - - If customization and flexibility are critical and your team prefers managing datasets manually for full control over each dataset creation process. ## Common questions ### What is the difference between automl-gs and FastDatasets? automl-gs: Automatically generate machine-learning models and code with input CSV and target field. FastDatasets: A powerful tool for creating high-quality training datasets for Large Language Models (LLMs). See the comparison table for live GitHub stats and shared categories. ### When should I choose automl-gs over FastDatasets? Choose automl-gs over FastDatasets when License: automl-gs is MIT, FastDatasets is Apache-2.0; Tags unique to automl-gs: automl, keras, machine-learning, tensorflow; Need to rapidly prototype models with limited ML expertise. ### When should I choose FastDatasets over automl-gs? Choose FastDatasets over automl-gs when License: FastDatasets is Apache-2.0, automl-gs is MIT; Tags unique to FastDatasets: asyncio, dataset-generation, datasets, llm; - When you need to generate datasets specifically tailored to improve the performance of LLMs. ### When should I avoid automl-gs? Complex feature engineering or non-standard data inputs required Sensitive about licensing of the generated code ### When should I avoid FastDatasets? - Avoid using if the project does not involve training or fine-tuning LLMs as its primary objective. - If customization and flexibility are critical and your team prefers managing datasets manually for full control over each dataset creation process. ### Is automl-gs or FastDatasets more popular on GitHub? automl-gs has more GitHub stars (1,869 vs 222). Stars measure visibility, not whether either tool fits your constraints. ### Are automl-gs and FastDatasets open source? Yes - both are open-source projects on GitHub (automl-gs: MIT, FastDatasets: Apache-2.0). ### Where can I find alternatives to automl-gs or FastDatasets? GraphCanon lists graph-backed alternatives at [automl-gs alternatives](/tools/minimaxir-automl-gs/alternatives) and [FastDatasets alternatives](/tools/zhulinsen-fastdatasets/alternatives) ([automl-gs markdown twin](/tools/minimaxir-automl-gs/alternatives.md), [FastDatasets markdown twin](/tools/zhulinsen-fastdatasets/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/minimaxir-automl-gs-vs-zhulinsen-fastdatasets.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, automl-gs or FastDatasets? automl-gs: Dormant. FastDatasets: Slowing. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for automl-gs and FastDatasets? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [automl-gs trust report](/tools/minimaxir-automl-gs/trust); [FastDatasets trust report](/tools/zhulinsen-fastdatasets/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=minimaxir-automl-gs`](/api/graphcanon/graph?tool=minimaxir-automl-gs) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_