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.
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.
What things you need to install the software and how to install them
Give examples
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
Explain how to run the automated tests for this system
Explain what these tests test and why
npm test
Explain what these tests test and why
Give an example
Add additional notes about how to deploy this on a live system
- tensorflow.js
- brain.js
- mocha unittest
Please read CONTRIBUTING.md for details on our code of conduct, and the process for submitting pull requests to us.
0.0.0
*Loai abdalslam - Initial work - Loai abdalslam
See also the list of contributors who participated in this project.
This project is licensed under the MIT License - see the LICENSE.md file for details