Machine Learning Toolbox 2

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  • License: MIT License
  • Author: PhilipMay
  • Tags optuna, deep learning, ml, ai, machine learning, hyperparameter optimization, hyperparameter tuning, nlp, natural language processing, transformers, llm, large-language-models, openai, plot
  • Requires: Python >=3.8, <4.0
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Project description

Machine Learning Toolbox 2 - MLTB2

MIT License Python Version pypi Poetry
pytest Static Code Checks Build & Deploy Doc GitHub issues

📦 A box of machine learning tools. 📦

Documentation Page

Installation

MLTB2 is available at the Python Package Index (PyPI). It can be installed with pip:

pip install mltb2

Some optional dependencies might be necessary. You can install all of them with:

pip install mltb2[files,fasttext,optuna,plot,somajo,transformers,somajo_transformers,openai]

If you don't want to install all dependencies, see the description of the individual modules.

Licensing

Copyright (c) 2023 Philip May
Copyright (c) 2023 Philip May, Deutsche Telekom AG

Licensed under the MIT License (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License by reviewing the file LICENSE in the repository.

Project details

Verified details

These details have been verified by PyPI
Maintainers
Avatar for Dieshe from gravatar.com Dieshe

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: MIT License
  • Author: PhilipMay
  • Tags optuna, deep learning, ml, ai, machine learning, hyperparameter optimization, hyperparameter tuning, nlp, natural language processing, transformers, llm, large-language-models, openai, plot
  • Requires: Python >=3.8, <4.0
Classifiers

Release history Release notifications | RSS feed

1.0.1

1.0.1rc3 pre-release

1.0.0

0.12.3

0.12.2

0.12.0

0.11.1

0.11.0

0.10.1rc1 pre-release

0.10.0

0.9.1rc1 pre-release

0.9.0

0.8.1

This version

0.8.0

0.7.4

0.7.3

0.7.1

0.7.0

0.6.0

0.5.0

0.4.4

0.4.3

0.4.2

0.4.0

0.3.0

0.2.0

0.0.7

0.0.6

0.0.5

0.0.4

0.0.3

0.0.2

0.0.1

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