Skip to main content

NeoML python bindings

Project description

NeoML

NeoML is an end-to-end machine learning framework that allows you to build, train, and deploy ML models. It provides many traditional ML algorithms and neural networks with support for over 100 layer types.

NeoML is designed to minimize your code's dependence on the platform and devices used for calculations. The low-level math functions are isolated in a separate math engine module that has different implementations for different platforms, and the high-level code only has to select an appropriate math engine implementation to work with.

Desktop Build Status Python Build iOS Build Documentation Status

Documentation

See our documentation that includes detailed API reference and tutorials demonstrating how to use the library at https://neoml.readthedocs.io

Install

pip3 install neoml

Project details


Download files

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

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

neoml-2.0.210-cp311-cp311-win_amd64.whl (7.7 MB view details)

Uploaded CPython 3.11 Windows x86-64

neoml-2.0.210-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (16.8 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ x86-64

neoml-2.0.210-cp311-cp311-macosx_11_0_x86_64.whl (6.0 MB view details)

Uploaded CPython 3.11 macOS 11.0+ x86-64

neoml-2.0.210-cp310-cp310-win_amd64.whl (7.7 MB view details)

Uploaded CPython 3.10 Windows x86-64

neoml-2.0.210-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (16.8 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ x86-64

neoml-2.0.210-cp310-cp310-macosx_11_0_universal2.whl (6.0 MB view details)

Uploaded CPython 3.10 macOS 11.0+ universal2 (ARM64, x86-64)

neoml-2.0.210-cp39-cp39-win_amd64.whl (7.7 MB view details)

Uploaded CPython 3.9 Windows x86-64

neoml-2.0.210-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (16.8 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ x86-64

neoml-2.0.210-cp39-cp39-macosx_11_0_universal2.whl (6.0 MB view details)

Uploaded CPython 3.9 macOS 11.0+ universal2 (ARM64, x86-64)

neoml-2.0.210-cp38-cp38-win_amd64.whl (7.7 MB view details)

Uploaded CPython 3.8 Windows x86-64

neoml-2.0.210-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (16.8 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ x86-64

neoml-2.0.210-cp38-cp38-macosx_11_0_x86_64.whl (6.0 MB view details)

Uploaded CPython 3.8 macOS 11.0+ x86-64

File details

Details for the file neoml-2.0.210-cp311-cp311-win_amd64.whl.

File metadata

  • Download URL: neoml-2.0.210-cp311-cp311-win_amd64.whl
  • Upload date:
  • Size: 7.7 MB
  • Tags: CPython 3.11, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.12

File hashes

Hashes for neoml-2.0.210-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 90a74de545da8c91fde1523b4dda7c2e2b7b1134a89317c1fa7745091ba7f307
MD5 4157bf64516b4cf94a68c0515dc8f653
BLAKE2b-256 0d389bbce7b7a27ba6ce83f46c3257d34aadf3ffbd4f20622eb6afcc63755dc3

See more details on using hashes here.

File details

Details for the file neoml-2.0.210-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for neoml-2.0.210-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 3c5516925a92eadcab7f9af2617ae6d76e6d74d2a8d513be72175af9041af32b
MD5 b1afaf7b241a1868022ddcb8373599e3
BLAKE2b-256 514fb93c8146db5340d8ea6458776e4e9281341635c35ae114e016bf67d5246b

See more details on using hashes here.

File details

Details for the file neoml-2.0.210-cp311-cp311-macosx_11_0_x86_64.whl.

File metadata

File hashes

Hashes for neoml-2.0.210-cp311-cp311-macosx_11_0_x86_64.whl
Algorithm Hash digest
SHA256 bcacd04e467d557a020c69398f6bbca2e648a1c4569546963383db39b13d3be8
MD5 7de81e31e59d5870cbbfc9b4c66a9b8c
BLAKE2b-256 e8abb73e1c1cb9a787221099377af0bd341fd79a24a3f0196b82950f22f4aa11

See more details on using hashes here.

File details

Details for the file neoml-2.0.210-cp310-cp310-win_amd64.whl.

File metadata

  • Download URL: neoml-2.0.210-cp310-cp310-win_amd64.whl
  • Upload date:
  • Size: 7.7 MB
  • Tags: CPython 3.10, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.12

File hashes

Hashes for neoml-2.0.210-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 80a7a0a8f41efc1e682f779301697ee282da35729c2207d7a4419058e8e65163
MD5 672640971133b491f076dd3330f17638
BLAKE2b-256 3b272705ae66acd89d4912c4d508f45fc677db974ad364e8505cb32cbde18547

See more details on using hashes here.

File details

Details for the file neoml-2.0.210-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for neoml-2.0.210-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 9a229bde09da0347b95420c3cc1ea80091238671ba00dda82b59de688d74c36d
MD5 29e3e02da7be002c34d6f2effe71ff58
BLAKE2b-256 f4379315751bcaca891da458bbd2e7f1dc9fe6ca4cb67235ca717047bf90fb76

See more details on using hashes here.

File details

Details for the file neoml-2.0.210-cp310-cp310-macosx_11_0_universal2.whl.

File metadata

File hashes

Hashes for neoml-2.0.210-cp310-cp310-macosx_11_0_universal2.whl
Algorithm Hash digest
SHA256 7ed93e7ea9f837d80ab5b88a3fd17aa58a9b52be99d7e9c9b7e0dfdb4ebea750
MD5 3531839e04cb6a243739290150d551d5
BLAKE2b-256 83043e8a88e735b366ce104e11ca6618008a0545b80a89335ce62d9b29b6e5a7

See more details on using hashes here.

File details

Details for the file neoml-2.0.210-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: neoml-2.0.210-cp39-cp39-win_amd64.whl
  • Upload date:
  • Size: 7.7 MB
  • Tags: CPython 3.9, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.12

File hashes

Hashes for neoml-2.0.210-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 f379634f7283bedfff429f8a82fb2742f940bfd77ee0aae7c1a01c4f9116827f
MD5 6244c8f8e3de3fa25e332183ba4eecae
BLAKE2b-256 331800a5c700f2fc8e8ec2a6d2987598fe58663cef903abeac759627429021bd

See more details on using hashes here.

File details

Details for the file neoml-2.0.210-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for neoml-2.0.210-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 94602d87941a34a89c7304818502e8d3c38ec9062e4bca646853e1033ed6eb44
MD5 dc8f0e2d230aa71a86fdddadd22bc895
BLAKE2b-256 a0d3724ddcf16ed37119db7988e99577e42f3b80cef043084316dcfd20c83943

See more details on using hashes here.

File details

Details for the file neoml-2.0.210-cp39-cp39-macosx_11_0_universal2.whl.

File metadata

File hashes

Hashes for neoml-2.0.210-cp39-cp39-macosx_11_0_universal2.whl
Algorithm Hash digest
SHA256 ee22454743a2d871d14781cc1159924bd4c1f980581036aa2d3f33680ba941cd
MD5 e33dda2d8e0a8449a97e29087b661cbb
BLAKE2b-256 ef36ad91344718f2706382aeb6d52d034d70d0f906e0fb0299c4e05821cf07cf

See more details on using hashes here.

File details

Details for the file neoml-2.0.210-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: neoml-2.0.210-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 7.7 MB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.12

File hashes

Hashes for neoml-2.0.210-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 0d21430f42db41dc7500bee74c19562fdd8cf86237f0ec1aca1c775f136ceb9d
MD5 0e66e67296cb220b96e1f34bbddf6621
BLAKE2b-256 db0ff98d161aa2c8cf0fb24495c1d916ff46d4d9895e7845863aae2e000bce20

See more details on using hashes here.

File details

Details for the file neoml-2.0.210-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for neoml-2.0.210-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 fb20cba5a316f122c910558ab4bdd1efe0c15c2ba1f84168e3ff45535dcbdba0
MD5 253cdbcfe8c67d2fc3c0b8d8fc15e10d
BLAKE2b-256 e6437a2496b95f28be4b9723b8de5d325a3d824fb8cd5b0babba5cd190155e92

See more details on using hashes here.

File details

Details for the file neoml-2.0.210-cp38-cp38-macosx_11_0_x86_64.whl.

File metadata

File hashes

Hashes for neoml-2.0.210-cp38-cp38-macosx_11_0_x86_64.whl
Algorithm Hash digest
SHA256 2a9fbd4b349d31700aefd96a674bcce07f945b82f8b80e1bce79899d7132a528
MD5 ee17520c77802c503ccf42f176c3fc17
BLAKE2b-256 ef3d3742c8d0ea08a32e3019aa6623341f545f1e1e0c5d1615eadd7c90dfb6a7

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