A pipeline library for testing and validating time series data
Project description
pypelearn
A pipeline for testing and validation of synthetic machine learning data
pypelearn is a Python framework for handling and processing high-dimensional time series data.
For full documentation, please visit https://harston.io/pypelearn
pypelearn utilises numpy, pandas, matplotlib, and statsmodels to allow linear and nonlinear modelling of high-dimensional time series tensors.
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
pypelearn-0.0.20.tar.gz
(9.8 kB
view details)
Built Distribution
File details
Details for the file pypelearn-0.0.20.tar.gz.
File metadata
- Download URL: pypelearn-0.0.20.tar.gz
- Upload date:
- Size: 9.8 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/1.11.0 pkginfo/1.4.2 requests/2.19.1 setuptools/39.2.0 requests-toolbelt/0.8.0 tqdm/4.26.0 CPython/3.6.5
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 66a0076a3cee50fcd480a9417af0a1cf1de578dfdde69a555f9be2ccd4a948ea |
|
| MD5 | ebbffc10906cf26027944a153b1fd439 |
|
| BLAKE2b-256 | 0dfd24ee0eb784a00be25ea69020c128cfc3645fa72377b8e2dfec252fd5edd3 |
File details
Details for the file pypelearn-0.0.20-py3-none-any.whl.
File metadata
- Download URL: pypelearn-0.0.20-py3-none-any.whl
- Upload date:
- Size: 11.3 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/1.11.0 pkginfo/1.4.2 requests/2.19.1 setuptools/39.2.0 requests-toolbelt/0.8.0 tqdm/4.26.0 CPython/3.6.5
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | d9d9a69ee96e20bdbd2e5fe9bdfe65ac53bcc6027efcaa21415212d61ac19bc2 |
|
| MD5 | bfcaa85f7f5b6fd3d318b7555eeb1f29 |
|
| BLAKE2b-256 | b1bb3888bb0dd1c58ccf837ee43c8dc87765ffc328a9d0148cad50d37e61454e |
