Metadata-Version: 2.1
Name: mltu
Version: 1.0.5
Summary: Machine Learning Training Utilities (MLTU) for TenosrFlow and PyTorch
Home-page: https://pylessons.com/
Author: PyLessons
Author-email: pythonlessons0@gmail.com
Project-URL: Source, https://github.com/pythonlessons/mltu/
Project-URL: Tracker, https://github.com/pythonlessons/mltu/issues
Requires-Python: >=3
Description-Content-Type: text/markdown
Provides-Extra: gpu
License-File: LICENSE

# MLTU - Machine Learning Training Utilities
Machine Learning Training Utilities for <b>TensorFlow 2.*</b> and <b>PyTorch</b> with Python 3
<p align="center">
  <img src="https://pylessons.com/media/Tutorials/mltu/machine-learning-training-utilities.png">
</p>

# Installation:
To use MLTU in your own project, you can install it from PyPI:
```bash
pip install mltu
```
When running tutorials, it's necessary to install mltu for a specific tutorial, for example:
```bash
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](https://pylessons.com/mltu)
1. [Text Recognition With TensorFlow and CTC network](https://pylessons.com/ctc-text-recognition), code in ```Tutorials\01_image_to_word``` folder;
2. [TensorFlow OCR model for reading Captchas](https://pylessons.com/tensorflow-ocr-captcha), code in ```Tutorials\02_captcha_to_text``` folder;
3. [Handwriting words recognition with TensorFlow](https://pylessons.com/handwriting-recognition), code in ```Tutorials\03_handwriting_recognition``` folder;
4. [Handwritten sentence recognition with TensorFlow](https://pylessons.com/handwritten-sentence-recognition), code in ```Tutorials\04_sentence_recognition``` folder;
5. [Introduction to speech recognition with TensorFlow](https://pylessons.com/speech-recognition), code in ```Tutorials\05_speech_recognition``` folder;
6. [Introduction to PyTorch in a practical way](https://pylessons.com/pytorch-introduction), code in ```Tutorials\06_pytorch_introduction``` folder;
7. [Using custom wrapper to simplify PyTorch models training pipeline](https://pylessons.com/pytorch-introduction), code in ```Tutorials\07_pytorch_wrapper``` folder;
8. [Handwriting words recognition with PyTorch](https://pylessons.com/handwriting-recognition-pytorch), code in ```Tutorials\08_handwriting_recognition_torch``` folder;
