Skip to main content

Machine Learning Training Utilities (MLTU) for TensorFlow and PyTorch

Project description

MLTU - Machine Learning Training Utilities

Machine Learning Training Utilities for TensorFlow 2.* and PyTorch with Python 3

Installation:

To use MLTU in your own project, you can install it from PyPI:

pip install mltu

When running tutorials, it's necessary to install mltu for a specific tutorial, for example:

pip install mltu==0.1.3

Each tutorial has its own requirements.txt file for a specific mltu version. As this project progress, the newest versions may have breaking changes, so it's recommended to use the same version as in the tutorial.

Tutorials and Examples can be found on PyLessons.com

  1. Text Recognition With TensorFlow and CTC network, code in Tutorials\01_image_to_word folder;
  2. TensorFlow OCR model for reading Captchas, code in Tutorials\02_captcha_to_text folder;
  3. Handwriting words recognition with TensorFlow, code in Tutorials\03_handwriting_recognition folder;
  4. Handwritten sentence recognition with TensorFlow, code in Tutorials\04_sentence_recognition folder;
  5. Introduction to speech recognition with TensorFlow, code in Tutorials\05_speech_recognition folder;
  6. Introduction to PyTorch in a practical way, code in Tutorials\06_pytorch_introduction folder;
  7. Using custom wrapper to simplify PyTorch models training pipeline, code in Tutorials\07_pytorch_wrapper folder;
  8. Handwriting words recognition with PyTorch, code in Tutorials\08_handwriting_recognition_torch folder;
  9. Transformer training with TensorFlow for Translation task, code in Tutorials\09_translation_transformer folder;

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

mltu-1.1.0.tar.gz (33.8 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

mltu-1.1.0-py3-none-any.whl (39.6 kB view details)

Uploaded Python 3

File details

Details for the file mltu-1.1.0.tar.gz.

File metadata

  • Download URL: mltu-1.1.0.tar.gz
  • Upload date:
  • Size: 33.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.10.12

File hashes

Hashes for mltu-1.1.0.tar.gz
Algorithm Hash digest
SHA256 07a5598f5fa73ca2edf22cc7b282888bec258b49e8dac2cc2470201ad6123223
MD5 ee9acc2fa9e53c08984b09e9683d1647
BLAKE2b-256 f65c3211f726c250ef6c760745061e8b6903f424d0574575146a127e50a236d9

See more details on using hashes here.

File details

Details for the file mltu-1.1.0-py3-none-any.whl.

File metadata

  • Download URL: mltu-1.1.0-py3-none-any.whl
  • Upload date:
  • Size: 39.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.10.12

File hashes

Hashes for mltu-1.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 8aa686adb1566a23fa7d5d0420912a05049669d995aced598dcde404df1808c8
MD5 280b420a91cc46d231a3ae27b6158d80
BLAKE2b-256 8d19c406c0dfea1e5dd292f097fae3ea48d6c95fd062b1bb609ce30c86d16f57

See more details on using hashes here.

Supported by

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