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This is where I put things I find useful that speed up my work with Machine Learning. Ever looked in your old projects to reuse those cool functions you created before? Well, this repo is designed to be a Python Library of functions I created in my previous project that can be reused. I also share some Notebooks Tutorials and Python Code Snippets.
| Date | Stars |
|---|---|
| 2026-07-24 | 265 |
| 2026-07-25 | 265 |
| 2026-07-28 | 265 |
| 2026-07-30 | 265 |
| 2026-07-31 | 266 |
| 2026-08-06 | 266 |
Today
— stars today
This week
+1 stars this week
This month
— stars this month
Momentum
0.0
growth rate 0.38%/day
# Machine Learning Things
[](https://app.circleci.com/pipelines/github/gmihaila/ml_things)
[]()
[](https://opensource.org/licenses/Apache-2.0)
[]()
[](https://gmihaila.github.io/ml_things/)
[](https://github.com/gmihaila/ml_things/actions/workflows/pages/pages-build-deployment)
**Machine Learning Things** is a lightweight python library that contains functions and code snippets that
I use in my everyday research with Machine Learning, Deep Learning, NLP.
I created this repo because I was tired of always looking up same code from older projects and I wanted to gain some experience in building a Python library.
By making this available to everyone it gives me easy access to code I use frequently and it can help others in their machine learning work.
If you find any bugs or something doesn't make sense please feel free to open an issue.
That is not all! This library also contains Python code snippets and notebooks that speed up my Machine Learning workflow.
**Note:**
* **Update:** `Feb 5, 2022` Thank you all again for your support and kindness! This package is available on pypi now! `pip install ml-things`
* **Update:** `July 16, 2021` Thank you all for your support and kindness! As I promissed I will move this repo to pip install modules.
* If I reach 100 stars I will release the first official version and add it to the pip install modules!
# Table of contents
* **[ML_things](https://github.com/gmihaila/ml_things#ml_things)**:
* **[Installation](https://github.com/gmihaila/ml_things#installation)** Details on how to install **ml_things**.
* **[Array Functions](https://github.com/gmihaila/ml_things#array-functions)** Details on the **ml_things** array related functions:
* [pad_array](https://github.com/gmihaila/ml_things#pad_array-source)
* [batch_array](https://github.com/gmihaila/ml_things#batch_array-source)
* **[Plot Functions](https://github.com/gmihaila/ml_things#plot-functions)** Details on the **ml_things** plot related functions:
* [plot_array](https://github.com/gmihaila/ml_things#plot_array-source)
* [plot_dict](https://github.com/gmihaila/ml_things#plot_dict-source)
* [plot_confusion_matrix](https://github.com/gmihaila/ml_things#plot_confusion_matrix-source)
* **[Text Functions](https://github.com/gmihaila/ml_things#text-functions)** Details on the **ml_things** text related functions:
* [clean_text](https://github.com/gmihaila/ml_things#clean_text-source)
* **[Web Related](https://github.com/gmihaila/ml_things#web-related)** Details on the **ml_things** web related functions:
* [download_from](https://github.com/gmihaila/ml_things#download_from-source)
* **[Snippets](https://github.com/gmihaila/ml_things#snippets)**: Curated list of Python snippets I frequently use.
* **[Comments](https://github.com/gmihaila/ml_things#comments)**: Sample on how I like to comment my code. It is still a work in progress.
* **[Notebooks Tutorials](https://github.com/gmihaila/ml_things#notebooks-tutorials)**: Machine learning projects that I converted to tutorials and posted online.
* **[Final Note](https://github.com/gmihaila/ml_things#final-note)**: Being grateful.
<br/>
# ML_things
## Installation
This repo is tested with Python 3.6+.
It's always good practice to install `ml_things` in a [virtual environment](https://docs.python.org/3/library/venv.html). If you guidance on using Python's virtual enExcerpt of 19,689 characters
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