HIPS / autograd
Efficiently computes derivatives of NumPy code.
Why this job: topics: neural-network, autograd, jax, deep-learning, machine-learning
What it does
We can continue to differentiate as many times as we like, and use numpy's vectorization of scalar-valued functions across many different input values:
Get started
pip install autograd- Maintenance
- Active
- Last commit 7 days ago
- Stars
- 7,553
- +2 this week
- Licence
- MIT
- Allows business use
- Downloads for
- None listed
- No release files
- Latest version
- v1.9.1
- Released 4 months ago
- Built with
- Python
- 100% of the code
Is it looked after?
- Contributors
- Not stated
- Last 90 days
- Issues
- 60% closed
- 175 still open
- Pull requests
- 317 merged
- 69 waiting
- Releases
- 5
- 2 in the last year
- Contributing guide (opens in new tab)
- No security policy
- No code of conduct
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More: languages, topics and project record
Languages
- Python 100%
- Shell <1%
Topics
- autograd
- automatic-differentiation
- numpy
- python
- deep-learning
- derivative
- jax
- machine-learning
- neural-network
- numpy-arrays
- scipy
- ufunc
Project record
- JobAI libraries and models
- StatusListed
- Commits1,581
- Forks957
- Watching204
- Stars in 28 days+13
- CreatedNov 24, 2014
- First seen by usNov 7, 2026
- CheckedNov 10, 2026