https://github.com/loaiabdalslam/aul
Automated Deep learning & Machine Learning in JavaScript, in browser locally or in node.
https://github.com/loaiabdalslam/aul
auto-ml automated automated-machine-learning brain-js deep-learning machine-learning tensorflow
Last synced: about 1 year ago
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Automated Deep learning & Machine Learning in JavaScript, in browser locally or in node.
- Host: GitHub
- URL: https://github.com/loaiabdalslam/aul
- Owner: loaiabdalslam
- Created: 2019-07-31T22:02:03.000Z (almost 7 years ago)
- Default Branch: master
- Last Pushed: 2022-12-30T18:22:13.000Z (over 3 years ago)
- Last Synced: 2025-03-27T16:51:04.713Z (about 1 year ago)
- Topics: auto-ml, automated, automated-machine-learning, brain-js, deep-learning, machine-learning, tensorflow
- Language: JavaScript
- Homepage:
- Size: 186 KB
- Stars: 5
- Watchers: 1
- Forks: 1
- Open Issues: 7
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Automated Neural Network
Nowadays, machine learning techniques and algorithms are
employed in almost every application domain (e.g., financial
applications, advertising, recommendation systems, user behavior analytics). In practice, they are playing a crucial role
in harnessing the power of massive amounts of data which
we are currently producing every day in our digital world. In
general, the process of building a high-quality machine learning model is an iterative, complex and time-consuming process that involves trying different algorithms and techniques
in addition to having a good experience with effectively tuning their hyper-parameters. In particular, conducting this
process efficiently requires solid knowledge and experience
with the various techniques that can be employed. With the
continuous and vast increase of the amount of data in our
digital world, it has been acknowledged that the number of
knowledgeable data scientists can not scale to address these
challenges. Thus, there was a crucial need for automating
the process of building good machine learning models. In the
last few years, several techniques and frameworks have been
introduced to tackle the challenge of automating the process of Combined Algorithm Selection and Hyper-parameter
tuning (CASH) in the machine learning domain. The main
aim of these techniques is to reduce the role of human in the
loop and fill the gap for non-expert machine learning users
by playing the role of the domain expert.
## Getting Started
These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.
### Prerequisites
What things you need to install the software and how to install them
```
Give examples
```
### Installing
A step by step series of examples that tell you how to get a development env running
Say what the step will be
```
npm install
```
And repeat
```
until finished
```
End with an example of getting some data out of the system or using it for a little demo
## Running the tests
Explain how to run the automated tests for this system
### Break down into end to end tests
Explain what these tests test and why
```
npm test
```
### And coding style tests
Explain what these tests test and why
```
Give an example
```
## Deployment
Add additional notes about how to deploy this on a live system
## Built With
* tensorflow.js
* brain.js
* mocha unittest
## Contributing
Please read [CONTRIBUTING.md]() for details on our code of conduct, and the process for submitting pull requests to us.
## Versioning
0.0.0
## Authors
**Loai abdalslam* - *Initial work* - [Loai abdalslam](https://github.com/loaiabdalslam)
See also the list of [contributors](https://github.com/loaiabdalslam/ANN.js/contributors) who participated in this project.
## License
This project is licensed under the MIT License - see the [LICENSE.md](LICENSE.md) file for details
## Acknowledgments
* [Read more about automated machine learning ](https://github.com/hibayesian/awesome-automl-papers)
* [Automated Machine Learning Topic ](https://www.google.com/search?q=automated+machine+learing+papers&oq=automated+machine+learing+papers&aqs=chrome..69i57j0l5.5021j0j9&sourceid=chrome&ie=UTF-8)