dr-doc-search lets users converse with a book in PDF form using GPT-3.
Open source
24 alternativesAutoPyTorch
Automatic architecture search and hyperparameter optimization for PyTorch.
About AutoPyTorch
Auto-PyTorch is an open-source tool that jointly optimizes neural network architecture and training hyperparameters for PyTorch to enable automated deep learning. It uses SMAC for optimization with Hyperband budget rules, portfolio warm-starting, and ensemble building from evaluated configurations.
It is mainly developed for tabular classification and regression and time series forecasting. Version 0.1.0 breaks compatibility with v0.0.2, and forecasting use requires additional dependencies.
Key features
- Jointly optimizes network architecture and training hyperparameters
- Supports tabular classification and regression tasks
- Supports time series forecasting tasks
- Warm-starts SMAC search with greedy portfolio
- Builds ensemble from evaluated configurations
- Processes categorical data and supports cross-validation or holdout
Best for: Python users and researchers automating PyTorch models for tabular or time-series tasks.
Good for
- Jointly optimizes architecture and training hyperparameters
- Supports tabular classification, regression and time-series forecasting
- Warm-starts search with portfolio and builds ensemble from results
Watch out for
- Version 0.1.0 breaks compatibility with v0.0.2
- Forecasting installation requires additional dependencies
- Current version only supports greedy portfolio
AutoPyTorch at a glance
- Category
- AI & Machine Learning › AI Search & Research
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Yes · Source code
- Language
- English
- Last checked
- Oct 5, 2026 · Online when checked
- Listed
- Oct 5, 2026
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AutoPyTorch FAQ
What data does Auto-PyTorch support?
Tabular data for classification and regression, and time series data for forecasting.
How do I install it for forecasting?
Use pip install autoPyTorch[forecasting] to include the additional forecasting dependencies.
Is version 0.1.0 compatible with v0.0.2?
No, moving from v0.0.2 to v0.1.0 breaks compatibility; the old API is available at master_old.
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