# mlrose-ky: Machine Learning, Randomized Optimization, and SEarch
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`mlrose-ky` is a Python package for applying some of the most common randomized optimization and search algorithms to a range of different
optimization problems, over both discrete- and continuous-valued parameter spaces.
## Project Background
`mlrose-ky` is a fork of the [`mlrose-hiive`](https://github.com/hiive/mlrose) repository, which itself was a fork of the
original [`mlrose`](https://github.com/gkhayes/mlrose) repository.
The original `mlrose` was developed to support students of Georgia Tech's OMSCS/OMSA offering of CS 7641: Machine Learning.
Later, `mlrose-hiive` introduced a number of improvements (for example, the `Runners` submodule) and bug fixes on top of `mlrose`, though it
lacked documentation, contained some mysterious bugs and inefficiencies, and was unmaintained as of around 2022.
Today, `mlrose-ky` introduces additional improvements and bug fixes on top of `mlrose-hiive`. Some of these improvements include:
- Added documentation to every class, method, and function (i.e., descriptive docstrings, strong type-hints, and comments)
- New documentation available here: https://nkapila6.github.io/mlrose-ky/
- Increased test coverage from ~5% to ~99% (and still aiming for 100% coverage)
- Actively being maintained
- Fully backwards compatible with `mlrose-hiive`
- Optimized Python code with NumPy vectorization
## Main Features
This repository includes implementations of all randomized optimization algorithms taught in the course, as well as functionality to apply
these algorithms to integer-string optimization problems, such as N-Queens and the Knapsack problem; continuous-valued optimization
problems, such as the neural network weight problem; and tour optimization problems, such as the Travelling Salesperson problem. It also has
the flexibility to solve user-defined optimization problems.
### *Randomized Optimization Algorithms*
- Implementations of: hill climbing, randomized hill climbing, simulated annealing, genetic algorithm, and (discrete) MIMIC;
- Solve both maximization and minimization problems;
- Define the algorithm's initial state or start from a random state;
- Define your own simulated annealing decay schedule or use one of three pre-defined, customizable decay schedules: geometric decay,
arithmetic decay, or exponential decay.
### *Problem Types*
- Solve discrete-value (bit-string and integer-string), continuous-value, and tour optimization (travelling salesperson) problems;
- Define your own fitness function for optimization or use a pre-defined function.
- Pre-defined fitness functions exist for solving the: One Max, Flip Flop, Four Peaks, Six Peaks, Continuous Peaks, Knapsack, Travelling
Salesperson, N-Queens, and Max-K Color optimization problems.
### *Machine Learning Weight Optimization*
- Optimize the weights of neural networks, linear regression models, and logistic regression models using randomized hill climbing,
simulated annealing, the genetic algorithm, or gradient descent;
- Supports classification and regression neural networks.
## Project Improvements and Updates
The `mlrose-ky` project is undergoing significant improvements to enhance code quality, documentation, and testing. Below is a list of tasks
that have been completed or are in progress:
1. **Fix Python Warnings and Errors**: All Python warnings and errors have been addressed, except for a few unavoidable ones like "duplicate
code." ✅
2. **Add Python 3.10 Type Hints**: Type hints are being added to all function and method definitions, as well as method properties (
e.g., `self.foo: str = 'bar'`), to improve code clarity and maintainability. ✅
3. **Enhance Documentation**: NumPy-style docstrings are being added to all functions and methods, with at least a one-line docstring at the
top of every file summarizing its contents. This will make the codebase more understandable and easier to use for others. ✅
4. **Increase Test Coverage**: Tests are being added using Pytest, with a goal of achieving 100% code coverage to ensure the robustness of
the codebase. ✅
5. **Resolve TODO/FIXME Comments**: A thorough search is being conducted for any TODO, FIXME, or similar comments, and their respective
issues are being resolved. ✅
6. **Optimize Code**: Vanilla Python loops are being optimized where possible by vectorizing them with NumPy to enhance performance.
7. **Improve Code Quality**: Any other sub-optimal code, bugs, or code quality issues are being addressed to ensure a high standard of
coding practices. ✅
8. **Clean Up Codebase**: All commented-out code is being removed to keep the codebase clean and maintainable. ✅
## Installation
`mlrose-ky` was written in Python 3 and requires NumPy, SciPy, and Scikit-Learn (sklearn).
The latest version can be installed using `pip`:
```bash
pip install mlrose-ky --upgrade
```
Once it is installed, simply import it like so:
```python
import mlrose_ky as mlrose
```
## Documentation
The official `mlrose-ky` documentation can be found [here](https://nkapila6.github.io/mlrose-ky/).
A Jupyter notebook containing the examples used in the documentation is also
available [here](https://github.com/gkhayes/mlrose/blob/master/tutorial_examples.ipynb).
## Licensing, Authors, Acknowledgements
`mlrose-ky` was forked from the `mlrose-hiive` repository, which was a fork of the original `mlrose` repository.
The original `mlrose` was written by Genevieve Hayes and is distributed under
the [3-Clause BSD license](https://github.com/gkhayes/mlrose/blob/master/LICENSE).
You can cite `mlrose-ky` in research publications and reports as follows:
- Nakamura, K. (2024).
***mlrose-ky: Machine Learning, Randomized Optimization, and SEarch package for Python***. https://github.com/knakamura13/mlrose-ky/.
Accessed: *day month year*.
Please also keep the original authors' citations:
- Rollings, A. (2020).
***mlrose: Machine Learning, Randomized Optimization and SEarch package for Python, hiive extended remix***. https://github.com/hiive/mlrose. Accessed: *day month year*.
- Hayes, G. (2019).
***mlrose: Machine Learning, Randomized Optimization and SEarch package for Python***. https://github.com/gkhayes/mlrose. Accessed: *day
month year*.
Thanks to David S. Park for the MIMIC enhancements (from https://github.com/parkds/mlrose).
BibTeX entries:
```bibtex
@misc{Nakamura24,
author = {Nakamura, K.},
title = {{mlrose-ky: Machine Learning, Randomized Optimization and SEarch package for Python}},
year = 2024,
howpublished = {\url{https://github.com/knakamura13/mlrose-ky/}},
note = {Accessed: day month year}
}
@misc{Rollings20,
author = {Rollings, A.},
title = {{mlrose: Machine Learning, Randomized Optimization and SEarch package for Python, hiive extended remix}},
year = 2020,
howpublished = {\url{https://github.com/hiive/mlrose/}},
note = {Accessed: day month year}
}
@misc{Hayes19,
author = {Hayes, G.},
title = {{mlrose: Machine Learning, Randomized Optimization and SEarch package for Python}},
year = 2019,
howpublished = {\url{https://github.com/gkhayes/mlrose/}},
note = {Accessed: day month year}
}
```
## Collaborators
<!-- readme: collaborators -start -->
<table>
<tbody>
<tr>
<td align="center">
<a href="https://github.com/nkapila6">
<img src="https://avatars.githubusercontent.com/u/12816113?v=4" width="100;" alt="nkapila6"/>
<br />
<sub><b>Nikhil Kapila</b></sub>
</a>
</td>
<td align="center">
<a href="https://github.com/knakamura13">
<img src="https://avatars.githubusercontent.com/u/20162718?v=4" width="100;" alt="knakamura13"/>
<br />
<sub><b>Kyle Nakamura</b></sub>
</a>
</td>
<td align="center">
<a href="https://github.com/gitongah">
<img src="https://avatars.githubusercontent.com/u/39062444?v=4" width="100;" alt="gitongah"/>
<br />
<sub><b>Edwin Mbaabu</b></sub>
</a>
</td>
</tr>
<tbody>
</table>
<!-- readme: collaborators -end -->
## Contributors
<!-- readme: contributors -start -->
<table>
<tbody>
<tr>
<td align="center">
<a href="https://github.com/knakamura13">
<img src="https://avatars.githubusercontent.com/u/20162718?v=4" width="100;" alt="knakamura13"/>
<br />
<sub><b>Kyle Nakamura</b></sub>
</a>
</td>
<td align="center">
<a href="https://github.com/hiive">
<img src="https://avatars.githubusercontent.com/u/24660532?v=4" width="100;" alt="hiive"/>
<br />
<sub><b>hiive</b></sub>
</a>
</td>
<td align="center">
<a href="https://github.com/gkhayes">
<img src="https://avatars.githubusercontent.com/u/24857299?v=4" width="100;" alt="gkhayes"/>
<br />
<sub><b>Dr Genevieve Hayes</b></sub>
</a>
</td>
<td align="center">
<a href="https://github.com/ChristopherBilg">
<img src="https://avatars.githubusercontent.com/u/3654150?v=4" width="100;" alt="ChristopherBilg"/>
<br />
<sub><b>Chris Bilger</b></sub>
</a>
</td>
<td align="center">
<a href="https://github.com/nkapila6">
<img src="https://avatars.githubusercontent.com/u/12816113?v=4" width="100;" alt="nkapila6"/>
<br />
<sub><b>Nikhil Kapila</b></sub>
</a>
</td>
<td align="center">
<a href="https://github.com/gitongah">
<img src="https://avatars.githubusercontent.com/u/39062444?v=4" width="100;" alt="gitongah"/>
<br />
<sub><b>Edwin Mbaabu</b></sub>
</a>
</td>
</tr>
<tr>
<td align="center">
<a href="https://github.com/Agrover112">
<img src="https://avatars.githubusercontent.com/u/42321810?v=4" width="100;" alt="Agrover112"/>
<br />
<sub><b>Agrover112</b></sub>
</a>
</td>
<td align="center">
<a href="https://github.com/domfrecent">
<img src="https://avatars.githubusercontent.com/u/12631209?v=4" width="100;" alt="domfrecent"/>
<br />
<sub><b>Dominic Frecentese</b></sub>
</a>
</td>
<td align="center">
<a href="https://github.com/harrisonfloam">
<img src="https://avatars.githubusercontent.com/u/130672912?v=4" width="100;" alt="harrisonfloam"/>
<br />
<sub><b>harrisonfloam</b></sub>
</a>
</td>
<td align="center">
<a href="https://github.com/AlexWendland">
<img src="https://avatars.githubusercontent.com/u/3949212?v=4" width="100;" alt="AlexWendland"/>
<br />
<sub><b>Alex Wendland</b></sub>
</a>
</td>
<td align="center">
<a href="https://github.com/cooknl">
<img src="https://avatars.githubusercontent.com/u/5116899?v=4" width="100;" alt="cooknl"/>
<br />
<sub><b>CAPN</b></sub>
</a>
</td>
<td align="center">
<a href="https://github.com/KevinJBoyer">
<img src="https://avatars.githubusercontent.com/u/31424131?v=4" width="100;" alt="KevinJBoyer"/>
<br />
<sub><b>Kevin Boyer</b></sub>
</a>
</td>
</tr>
<tr>
<td align="center">
<a href="https://github.com/parkds">
<img src="https://avatars.githubusercontent.com/u/10566599?v=4" width="100;" alt="parkds"/>
<br />
<sub><b>David</b></sub>
</a>
</td>
<td align="center">
<a href="https://github.com/davideasaf">
<img src="https://avatars.githubusercontent.com/u/11589969?v=4" width="100;" alt="davideasaf"/>
<br />
<sub><b>David Asaf</b></sub>
</a>
</td>
<td align="center">
<a href="https://github.com/jfs42">
<img src="https://avatars.githubusercontent.com/u/43157283?v=4" width="100;" alt="jfs42"/>
<br />
<sub><b>Jason Seeley</b></sub>
</a>
</td>
<td align="center">
<a href="https://github.com/sareini">
<img src="https://avatars.githubusercontent.com/u/26151060?v=4" width="100;" alt="sareini"/>
<br />
<sub><b>Muhammad Sareini</b></sub>
</a>
</td>
<td align="center">
<a href="https://github.com/nibelungvalesti">
<img src="https://avatars.githubusercontent.com/u/9278042?v=4" width="100;" alt="nibelungvalesti"/>
<br />
<sub><b>nibelungvalesti</b></sub>
</a>
</td>
<td align="center">
<a href="https://github.com/tadmorgan">
<img src="https://avatars.githubusercontent.com/u/4197132?v=4" width="100;" alt="tadmorgan"/>
<br />
<sub><b>W. Tad Morgan</b></sub>
</a>
</td>
</tr>
<tr>
<td align="center">
<a href="https://github.com/mjschock">
<img src="https://avatars.githubusercontent.com/u/1357197?v=4" width="100;" alt="mjschock"/>
<br />
<sub><b>Michael Schock</b></sub>
</a>
</td>
<td align="center">
<a href="https://github.com/jlm429">
<img src="https://avatars.githubusercontent.com/u/10093986?v=4" width="100;" alt="jlm429"/>
<br />
<sub><b>John Mansfield</b></sub>
</a>
</td>
<td align="center">
<a href="https://github.com/dstrube1">
<img src="https://avatars.githubusercontent.com/u/7396679?v=4" width="100;" alt="dstrube1"/>
<br />
<sub><b>David Strube</b></sub>
</a>
</td>
<td align="center">
<a href="https://github.com/austin-bowen">
<img src="https://avatars.githubusercontent.com/u/4653828?v=4" width="100;" alt="austin-bowen"/>
<br />
<sub><b>Austin Bowen</b></sub>
</a>
</td>
<td align="center">
<a href="https://github.com/bspivey">
<img src="https://avatars.githubusercontent.com/u/6569966?v=4" width="100;" alt="bspivey"/>
<br />
<sub><b>Ben Spivey</b></sub>
</a>
</td>
<td align="center">
<a href="https://github.com/dreadn0ught">
<img src="https://avatars.githubusercontent.com/u/31293924?v=4" width="100;" alt="dreadn0ught"/>
<br />
<sub><b>David</b></sub>
</a>
</td>
</tr>
<tr>
<td align="center">
<a href="https://github.com/brokensandals">
<img src="https://avatars.githubusercontent.com/u/328868?v=4" width="100;" alt="brokensandals"/>
<br />
<sub><b>Jacob Williams</b></sub>
</a>
</td>
<td align="center">
<a href="https://github.com/vpipkt">
<img src="https://avatars.githubusercontent.com/u/7798319?v=4" width="100;" alt="vpipkt"/>
<br />
<sub><b>Jason T Brown</b></sub>
</a>
</td>
<td align="center">
<a href="https://github.com/zerolinux5">
<img src="https://avatars.githubusercontent.com/u/1896803?v=4" width="100;" alt="zerolinux5"/>
<br />
<sub><b> Jesus Magana</b></sub>
</a>
</td>
<td align="center">
<a href="https://github.com/ksbeattie">
<img src="https://avatars.githubusercontent.com/u/1534843?v=4" width="100;" alt="ksbeattie"/>
<br />
<sub><b>Keith Beattie</b></sub>
</a>
</td>
<td align="center">
<a href="https://github.com/MatthewCaseres">
<img src="https://avatars.githubusercontent.com/u/43053796?v=4" width="100;" alt="MatthewCaseres"/>
<br />
<sub><b>Matthew Caseres</b></sub>
</a>
</td>
<td align="center">
<a href="https://github.com/cbhyphen">
<img src="https://avatars.githubusercontent.com/u/12734117?v=4" width="100;" alt="cbhyphen"/>
<br />
<sub><b>cbhyphen</b></sub>
</a>
</td>
</tr>
<tr>
<td align="center">
<a href="https://github.com/dsctt">
<img src="https://avatars.githubusercontent.com/u/45729071?v=4" width="100;" alt="dsctt"/>
<br />
<sub><b>Daniel Scott</b></sub>
</a>
</td>
<td align="center">
<a href="https://github.com/wyang36">
<img src="https://avatars.githubusercontent.com/u/5606561?v=4" width="100;" alt="wyang36"/>
<br />
<sub><b>Kira Yang</b></sub>
</a>
</td>
</tr>
<tbody>
</table>
<!-- readme: contributors -end -->
Raw data
{
"_id": null,
"home_page": null,
"name": "mlrose-ky",
"maintainer": null,
"docs_url": null,
"requires_python": ">=3.10",
"maintainer_email": "Kyle Nakamura <knakamura13dev@gmail.com>",
"keywords": "machine learning, ML, randomized optimization, search algorithms, neural networks, genetic algorithm, simulated annealing, hill climbing, MIMIC, Python, OMSCS, CS, 7641, mlrose-hiive, mlrose-ky",
"author": null,
"author_email": "Kyle Nakamura <knakamura13dev@gmail.com>",
"download_url": "https://files.pythonhosted.org/packages/d9/12/db9f576553caa2df5b435a8e941ff29426c199e5aaee28b6967a97d4682a/mlrose_ky-1.1.6.tar.gz",
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"description": "# mlrose-ky: Machine Learning, Randomized Optimization, and SEarch\n\n[](https://pypi.org/project/mlrose-ky/)\n[](https://app.codacy.com/gh/knakamura13/mlrose-ky?utm_source=github.com&utm_medium=referral&utm_content=knakamura13/mlrose-ky&utm_campaign=Badge_Grade)\n[](https://app.codacy.com/gh/knakamura13/mlrose-ky/dashboard?utm_source=gh&utm_medium=referral&utm_content=&utm_campaign=Badge_coverage)\n[](https://wakatime.com/badge/user/3e093fe5-ba7b-427a-b7f6-22e93ae34ce8/project/7953f1b0-1775-4be1-92c7-13ee3a8dcc81)\n\n`mlrose-ky` is a Python package for applying some of the most common randomized optimization and search algorithms to a range of different\noptimization problems, over both discrete- and continuous-valued parameter spaces.\n\n## Project Background\n\n`mlrose-ky` is a fork of the [`mlrose-hiive`](https://github.com/hiive/mlrose) repository, which itself was a fork of the\noriginal [`mlrose`](https://github.com/gkhayes/mlrose) repository.\n\nThe original `mlrose` was developed to support students of Georgia Tech's OMSCS/OMSA offering of CS 7641: Machine Learning.\n\nLater, `mlrose-hiive` introduced a number of improvements (for example, the `Runners` submodule) and bug fixes on top of `mlrose`, though it\nlacked documentation, contained some mysterious bugs and inefficiencies, and was unmaintained as of around 2022.\n\nToday, `mlrose-ky` introduces additional improvements and bug fixes on top of `mlrose-hiive`. Some of these improvements include:\n\n- Added documentation to every class, method, and function (i.e., descriptive docstrings, strong type-hints, and comments)\n- New documentation available here: https://nkapila6.github.io/mlrose-ky/\n- Increased test coverage from ~5% to ~99% (and still aiming for 100% coverage)\n- Actively being maintained\n- Fully backwards compatible with `mlrose-hiive`\n- Optimized Python code with NumPy vectorization\n\n## Main Features\n\nThis repository includes implementations of all randomized optimization algorithms taught in the course, as well as functionality to apply\nthese algorithms to integer-string optimization problems, such as N-Queens and the Knapsack problem; continuous-valued optimization\nproblems, such as the neural network weight problem; and tour optimization problems, such as the Travelling Salesperson problem. It also has\nthe flexibility to solve user-defined optimization problems.\n\n### *Randomized Optimization Algorithms*\n\n- Implementations of: hill climbing, randomized hill climbing, simulated annealing, genetic algorithm, and (discrete) MIMIC;\n- Solve both maximization and minimization problems;\n- Define the algorithm's initial state or start from a random state;\n- Define your own simulated annealing decay schedule or use one of three pre-defined, customizable decay schedules: geometric decay,\n arithmetic decay, or exponential decay.\n\n### *Problem Types*\n\n- Solve discrete-value (bit-string and integer-string), continuous-value, and tour optimization (travelling salesperson) problems;\n- Define your own fitness function for optimization or use a pre-defined function.\n- Pre-defined fitness functions exist for solving the: One Max, Flip Flop, Four Peaks, Six Peaks, Continuous Peaks, Knapsack, Travelling\n Salesperson, N-Queens, and Max-K Color optimization problems.\n\n### *Machine Learning Weight Optimization*\n\n- Optimize the weights of neural networks, linear regression models, and logistic regression models using randomized hill climbing,\n simulated annealing, the genetic algorithm, or gradient descent;\n- Supports classification and regression neural networks.\n\n## Project Improvements and Updates\n\nThe `mlrose-ky` project is undergoing significant improvements to enhance code quality, documentation, and testing. Below is a list of tasks\nthat have been completed or are in progress:\n\n1. **Fix Python Warnings and Errors**: All Python warnings and errors have been addressed, except for a few unavoidable ones like \"duplicate\n code.\" \u2705\n\n2. **Add Python 3.10 Type Hints**: Type hints are being added to all function and method definitions, as well as method properties (\n e.g., `self.foo: str = 'bar'`), to improve code clarity and maintainability. \u2705\n\n3. **Enhance Documentation**: NumPy-style docstrings are being added to all functions and methods, with at least a one-line docstring at the\n top of every file summarizing its contents. This will make the codebase more understandable and easier to use for others. \u2705\n\n4. **Increase Test Coverage**: Tests are being added using Pytest, with a goal of achieving 100% code coverage to ensure the robustness of\n the codebase. \u2705\n\n5. **Resolve TODO/FIXME Comments**: A thorough search is being conducted for any TODO, FIXME, or similar comments, and their respective\n issues are being resolved. \u2705\n\n6. **Optimize Code**: Vanilla Python loops are being optimized where possible by vectorizing them with NumPy to enhance performance.\n\n7. **Improve Code Quality**: Any other sub-optimal code, bugs, or code quality issues are being addressed to ensure a high standard of\n coding practices. \u2705\n\n8. **Clean Up Codebase**: All commented-out code is being removed to keep the codebase clean and maintainable. \u2705\n\n## Installation\n\n`mlrose-ky` was written in Python 3 and requires NumPy, SciPy, and Scikit-Learn (sklearn).\n\nThe latest version can be installed using `pip`:\n\n```bash\npip install mlrose-ky --upgrade\n```\n\nOnce it is installed, simply import it like so:\n\n```python\nimport mlrose_ky as mlrose\n```\n\n## Documentation\n\nThe official `mlrose-ky` documentation can be found [here](https://nkapila6.github.io/mlrose-ky/).\n\nA Jupyter notebook containing the examples used in the documentation is also\navailable [here](https://github.com/gkhayes/mlrose/blob/master/tutorial_examples.ipynb).\n\n## Licensing, Authors, Acknowledgements\n\n`mlrose-ky` was forked from the `mlrose-hiive` repository, which was a fork of the original `mlrose` repository.\n\nThe original `mlrose` was written by Genevieve Hayes and is distributed under\nthe [3-Clause BSD license](https://github.com/gkhayes/mlrose/blob/master/LICENSE).\n\nYou can cite `mlrose-ky` in research publications and reports as follows:\n\n- Nakamura, K. (2024).\n ***mlrose-ky: Machine Learning, Randomized Optimization, and SEarch package for Python***. https://github.com/knakamura13/mlrose-ky/.\n Accessed: *day month year*.\n\nPlease also keep the original authors' citations:\n\n- Rollings, A. (2020).\n ***mlrose: Machine Learning, Randomized Optimization and SEarch package for Python, hiive extended remix***. https://github.com/hiive/mlrose. Accessed: *day month year*.\n- Hayes, G. (2019).\n ***mlrose: Machine Learning, Randomized Optimization and SEarch package for Python***. https://github.com/gkhayes/mlrose. Accessed: *day\n month year*.\n\nThanks to David S. Park for the MIMIC enhancements (from https://github.com/parkds/mlrose).\n\nBibTeX entries:\n\n```bibtex\n@misc{Nakamura24,\n author = {Nakamura, K.},\n title = {{mlrose-ky: Machine Learning, Randomized Optimization and SEarch package for Python}},\n year = 2024,\n howpublished = {\\url{https://github.com/knakamura13/mlrose-ky/}},\n note = {Accessed: day month year}\n}\n\n@misc{Rollings20,\n author = {Rollings, A.},\n title = {{mlrose: Machine Learning, Randomized Optimization and SEarch package for Python, hiive extended remix}},\n year = 2020,\n howpublished = {\\url{https://github.com/hiive/mlrose/}},\n note = {Accessed: day month year}\n}\n\n@misc{Hayes19,\n author = {Hayes, G.},\n title = {{mlrose: Machine Learning, Randomized Optimization and SEarch package for Python}},\n year = 2019,\n howpublished = {\\url{https://github.com/gkhayes/mlrose/}},\n note = {Accessed: day month year}\n}\n```\n\n## Collaborators\n\n<!-- readme: collaborators -start -->\n<table>\n\t<tbody>\n\t\t<tr>\n <td align=\"center\">\n <a href=\"https://github.com/nkapila6\">\n <img src=\"https://avatars.githubusercontent.com/u/12816113?v=4\" width=\"100;\" alt=\"nkapila6\"/>\n <br />\n <sub><b>Nikhil Kapila</b></sub>\n </a>\n </td>\n <td align=\"center\">\n <a href=\"https://github.com/knakamura13\">\n <img src=\"https://avatars.githubusercontent.com/u/20162718?v=4\" width=\"100;\" alt=\"knakamura13\"/>\n <br />\n <sub><b>Kyle Nakamura</b></sub>\n </a>\n </td>\n <td align=\"center\">\n <a href=\"https://github.com/gitongah\">\n <img src=\"https://avatars.githubusercontent.com/u/39062444?v=4\" width=\"100;\" alt=\"gitongah\"/>\n <br />\n <sub><b>Edwin Mbaabu</b></sub>\n </a>\n </td>\n\t\t</tr>\n\t<tbody>\n</table>\n<!-- readme: collaborators -end -->\n\n## Contributors\n\n<!-- readme: contributors -start -->\n<table>\n\t<tbody>\n\t\t<tr>\n <td align=\"center\">\n <a href=\"https://github.com/knakamura13\">\n <img src=\"https://avatars.githubusercontent.com/u/20162718?v=4\" width=\"100;\" alt=\"knakamura13\"/>\n <br />\n <sub><b>Kyle Nakamura</b></sub>\n </a>\n </td>\n <td align=\"center\">\n <a href=\"https://github.com/hiive\">\n <img src=\"https://avatars.githubusercontent.com/u/24660532?v=4\" width=\"100;\" alt=\"hiive\"/>\n <br />\n <sub><b>hiive</b></sub>\n </a>\n </td>\n <td align=\"center\">\n <a href=\"https://github.com/gkhayes\">\n <img src=\"https://avatars.githubusercontent.com/u/24857299?v=4\" width=\"100;\" alt=\"gkhayes\"/>\n <br />\n <sub><b>Dr Genevieve Hayes</b></sub>\n </a>\n </td>\n <td align=\"center\">\n <a href=\"https://github.com/ChristopherBilg\">\n <img src=\"https://avatars.githubusercontent.com/u/3654150?v=4\" width=\"100;\" alt=\"ChristopherBilg\"/>\n <br />\n <sub><b>Chris Bilger</b></sub>\n </a>\n </td>\n <td align=\"center\">\n <a href=\"https://github.com/nkapila6\">\n <img src=\"https://avatars.githubusercontent.com/u/12816113?v=4\" width=\"100;\" alt=\"nkapila6\"/>\n <br />\n <sub><b>Nikhil Kapila</b></sub>\n </a>\n </td>\n <td align=\"center\">\n <a href=\"https://github.com/gitongah\">\n <img src=\"https://avatars.githubusercontent.com/u/39062444?v=4\" width=\"100;\" alt=\"gitongah\"/>\n <br />\n <sub><b>Edwin Mbaabu</b></sub>\n </a>\n </td>\n\t\t</tr>\n\t\t<tr>\n <td align=\"center\">\n <a href=\"https://github.com/Agrover112\">\n <img src=\"https://avatars.githubusercontent.com/u/42321810?v=4\" width=\"100;\" alt=\"Agrover112\"/>\n <br />\n <sub><b>Agrover112</b></sub>\n </a>\n </td>\n <td align=\"center\">\n <a href=\"https://github.com/domfrecent\">\n <img src=\"https://avatars.githubusercontent.com/u/12631209?v=4\" width=\"100;\" alt=\"domfrecent\"/>\n <br />\n <sub><b>Dominic Frecentese</b></sub>\n </a>\n </td>\n <td align=\"center\">\n <a href=\"https://github.com/harrisonfloam\">\n <img src=\"https://avatars.githubusercontent.com/u/130672912?v=4\" width=\"100;\" alt=\"harrisonfloam\"/>\n <br />\n <sub><b>harrisonfloam</b></sub>\n </a>\n </td>\n <td align=\"center\">\n <a href=\"https://github.com/AlexWendland\">\n <img src=\"https://avatars.githubusercontent.com/u/3949212?v=4\" width=\"100;\" alt=\"AlexWendland\"/>\n <br />\n <sub><b>Alex Wendland</b></sub>\n </a>\n </td>\n <td align=\"center\">\n <a href=\"https://github.com/cooknl\">\n <img src=\"https://avatars.githubusercontent.com/u/5116899?v=4\" width=\"100;\" alt=\"cooknl\"/>\n <br />\n <sub><b>CAPN</b></sub>\n </a>\n </td>\n <td align=\"center\">\n <a href=\"https://github.com/KevinJBoyer\">\n <img src=\"https://avatars.githubusercontent.com/u/31424131?v=4\" width=\"100;\" alt=\"KevinJBoyer\"/>\n <br />\n <sub><b>Kevin Boyer</b></sub>\n </a>\n </td>\n\t\t</tr>\n\t\t<tr>\n <td align=\"center\">\n <a href=\"https://github.com/parkds\">\n <img src=\"https://avatars.githubusercontent.com/u/10566599?v=4\" width=\"100;\" alt=\"parkds\"/>\n <br />\n <sub><b>David</b></sub>\n </a>\n </td>\n <td align=\"center\">\n <a href=\"https://github.com/davideasaf\">\n <img src=\"https://avatars.githubusercontent.com/u/11589969?v=4\" width=\"100;\" alt=\"davideasaf\"/>\n <br />\n <sub><b>David Asaf</b></sub>\n </a>\n </td>\n <td align=\"center\">\n <a href=\"https://github.com/jfs42\">\n <img src=\"https://avatars.githubusercontent.com/u/43157283?v=4\" width=\"100;\" alt=\"jfs42\"/>\n <br />\n <sub><b>Jason Seeley</b></sub>\n </a>\n </td>\n <td align=\"center\">\n <a href=\"https://github.com/sareini\">\n <img src=\"https://avatars.githubusercontent.com/u/26151060?v=4\" width=\"100;\" alt=\"sareini\"/>\n <br />\n <sub><b>Muhammad Sareini</b></sub>\n </a>\n </td>\n <td align=\"center\">\n <a href=\"https://github.com/nibelungvalesti\">\n <img src=\"https://avatars.githubusercontent.com/u/9278042?v=4\" width=\"100;\" alt=\"nibelungvalesti\"/>\n <br />\n <sub><b>nibelungvalesti</b></sub>\n </a>\n </td>\n <td align=\"center\">\n <a href=\"https://github.com/tadmorgan\">\n <img src=\"https://avatars.githubusercontent.com/u/4197132?v=4\" width=\"100;\" alt=\"tadmorgan\"/>\n <br />\n <sub><b>W. Tad Morgan</b></sub>\n </a>\n </td>\n\t\t</tr>\n\t\t<tr>\n <td align=\"center\">\n <a href=\"https://github.com/mjschock\">\n <img src=\"https://avatars.githubusercontent.com/u/1357197?v=4\" width=\"100;\" alt=\"mjschock\"/>\n <br />\n <sub><b>Michael Schock</b></sub>\n </a>\n </td>\n <td align=\"center\">\n <a href=\"https://github.com/jlm429\">\n <img src=\"https://avatars.githubusercontent.com/u/10093986?v=4\" width=\"100;\" alt=\"jlm429\"/>\n <br />\n <sub><b>John Mansfield</b></sub>\n </a>\n </td>\n <td align=\"center\">\n <a href=\"https://github.com/dstrube1\">\n <img src=\"https://avatars.githubusercontent.com/u/7396679?v=4\" width=\"100;\" alt=\"dstrube1\"/>\n <br />\n <sub><b>David Strube</b></sub>\n </a>\n </td>\n <td align=\"center\">\n <a href=\"https://github.com/austin-bowen\">\n <img src=\"https://avatars.githubusercontent.com/u/4653828?v=4\" width=\"100;\" alt=\"austin-bowen\"/>\n <br />\n <sub><b>Austin Bowen</b></sub>\n </a>\n </td>\n <td align=\"center\">\n <a href=\"https://github.com/bspivey\">\n <img src=\"https://avatars.githubusercontent.com/u/6569966?v=4\" width=\"100;\" alt=\"bspivey\"/>\n <br />\n <sub><b>Ben Spivey</b></sub>\n </a>\n </td>\n <td align=\"center\">\n <a href=\"https://github.com/dreadn0ught\">\n <img src=\"https://avatars.githubusercontent.com/u/31293924?v=4\" width=\"100;\" alt=\"dreadn0ught\"/>\n <br />\n <sub><b>David</b></sub>\n </a>\n </td>\n\t\t</tr>\n\t\t<tr>\n <td align=\"center\">\n <a href=\"https://github.com/brokensandals\">\n <img src=\"https://avatars.githubusercontent.com/u/328868?v=4\" width=\"100;\" alt=\"brokensandals\"/>\n <br />\n <sub><b>Jacob Williams</b></sub>\n </a>\n </td>\n <td align=\"center\">\n <a href=\"https://github.com/vpipkt\">\n <img src=\"https://avatars.githubusercontent.com/u/7798319?v=4\" width=\"100;\" alt=\"vpipkt\"/>\n <br />\n <sub><b>Jason T Brown</b></sub>\n </a>\n </td>\n <td align=\"center\">\n <a href=\"https://github.com/zerolinux5\">\n <img src=\"https://avatars.githubusercontent.com/u/1896803?v=4\" width=\"100;\" alt=\"zerolinux5\"/>\n <br />\n <sub><b> Jesus Magana</b></sub>\n </a>\n </td>\n <td align=\"center\">\n <a href=\"https://github.com/ksbeattie\">\n <img src=\"https://avatars.githubusercontent.com/u/1534843?v=4\" width=\"100;\" alt=\"ksbeattie\"/>\n <br />\n <sub><b>Keith Beattie</b></sub>\n </a>\n </td>\n <td align=\"center\">\n <a href=\"https://github.com/MatthewCaseres\">\n <img src=\"https://avatars.githubusercontent.com/u/43053796?v=4\" width=\"100;\" alt=\"MatthewCaseres\"/>\n <br />\n <sub><b>Matthew Caseres</b></sub>\n </a>\n </td>\n <td align=\"center\">\n <a href=\"https://github.com/cbhyphen\">\n <img src=\"https://avatars.githubusercontent.com/u/12734117?v=4\" width=\"100;\" alt=\"cbhyphen\"/>\n <br />\n <sub><b>cbhyphen</b></sub>\n </a>\n </td>\n\t\t</tr>\n\t\t<tr>\n <td align=\"center\">\n <a href=\"https://github.com/dsctt\">\n <img src=\"https://avatars.githubusercontent.com/u/45729071?v=4\" width=\"100;\" alt=\"dsctt\"/>\n <br />\n <sub><b>Daniel Scott</b></sub>\n </a>\n </td>\n <td align=\"center\">\n <a href=\"https://github.com/wyang36\">\n <img src=\"https://avatars.githubusercontent.com/u/5606561?v=4\" width=\"100;\" alt=\"wyang36\"/>\n <br />\n <sub><b>Kira Yang</b></sub>\n </a>\n </td>\n\t\t</tr>\n\t<tbody>\n</table>\n<!-- readme: contributors -end -->\n",
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