Skip to main content

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

  • 09/02/2019: tfnumpy 0.0.6 released.
  • 07/07/2019: tfnumpy 0.0.5 released.
  • 05/18/2019: tfnumpy 0.0.4 released.
  • 04/25/2019: tfnumpy 0.0.3 released.
  • 01/19/2019: tfnumpy 0.0.2 released.
  • 11/05/2018: tfnumpy 0.0.1 released.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

tfnumpy-0.0.6.tar.gz (9.5 kB view details)

Uploaded Source

File details

Details for the file tfnumpy-0.0.6.tar.gz.

File metadata

  • Download URL: tfnumpy-0.0.6.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/2.18.4 setuptools/41.0.1 requests-toolbelt/0.8.0 tqdm/4.19.7 CPython/2.7.13

File hashes

Hashes for tfnumpy-0.0.6.tar.gz
Algorithm Hash digest
SHA256 77362c09be4b75ac5d7f5edef2414fa695dde708364caf8f99cf863f41c21a0a
MD5 c7ac71be6076324989c47a9651e71ccb
BLAKE2b-256 325ff17bc868fb7b85525ab8b43ffe2a4c815b6ef868d14600d9df3822d9f82b

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page