Collection of Simple Numerical Routines using TensorFlow
Project description
Numerical Python using TensorFlow
Functionalities:
- Embedding: Sammon algorithm;
- Linear regression (with Ridge, Lasso, and ElasticNet);
- Tensor products: Khatri-Rao product and Kronecker product;
- Tensor decomposition using ALS.
News
- 12/24/2019:
tfnumpy0.1.0 released. - 09/02/2019:
tfnumpy0.0.6 released. - 07/07/2019:
tfnumpy0.0.5 released. - 05/18/2019:
tfnumpy0.0.4 released. - 04/25/2019:
tfnumpy0.0.3 released. - 01/19/2019:
tfnumpy0.0.2 released. - 11/05/2018:
tfnumpy0.0.1 released.
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
tfnumpy-0.1.0.tar.gz
(9.5 kB
view details)
File details
Details for the file tfnumpy-0.1.0.tar.gz.
File metadata
- Download URL: tfnumpy-0.1.0.tar.gz
- Upload date:
- Size: 9.5 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/1.13.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.0.1 requests-toolbelt/0.8.0 tqdm/4.19.7 CPython/2.7.13
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | c363797aaf77ba78dacbc6892ca41c626f5ed1725bfc8430461e6be76c6dbe7d |
|
| MD5 | ebd5679794b5bd428cb7844a7edb9b20 |
|
| BLAKE2b-256 | 99239ea5cb985c6051e04dc6ffd4cb41667037aafc9f7c3216874b14f6c58b38 |
