Free and Open Machine Learning
Great that you are interested in this open collaboration project.
This project is all about collaborative learning on applying FOSS Machine Learning. This project is an open research project. It is open for all to join.
Since this project is a decentralized open learning project, to drive innovation, it is supported by BM-Support Foundation (https://www.bm-support.org/ ) If you are an open company, consider to join this Foundation! https://www.bm-support.org/open-company-principles/
This project is in alpha stage. However already planned spin-offs from this project are:
- Creating one or more open publications (cc-by-sa). Yes, lessons learned should be published or shared.
- Workshop and Tutorials
- Creating and developing a must known list of FOSS Machine Learning Frameworks and Tools available.
Goals of the project
One of the goals of the project is to develop and harvest ml-knowledge that is not (easily) available elsewhere or not available under an open license.
The Free and Open Machine Learning Book
We are in the process of writing a book on Machine Learning that motivates people to learn machine learning concepts and how machine learning can be used or tried in a simple way. This book is not intended to cover all advanced (mathematical) machine learning techniques or explaining ml specific software platforms. There are already some books doing this. Instead, we aim to provide the necessary knowledge that is required to start applying machine learning with success in large or small enterprises.
The main research questions for this project are:
- What problems can be more easily solved using machine learning applications?
- What are the main security,privacy and safety concerns when machine learning is applied and used more widely?
In order to be able to answer this questions an architecture framework is developed, where answers on the following questions will be harvested:
- Why is Free and Open Machine learning important?
- What business use cases are suited for applying machine learning?
- What are the main solution building blocks that make an vendor-neutral machine learning reference architecture?
- What capabilities are required to use and develop machine learning applications?
- What are good, quality and open resources for learning machine learning?
- What are the main building blocks of a open machine learning reference architecture?
- How to develop a solution architecture for machine learning applications?
- What are the main OSS machine learning frameworks and applications?
- How can machine learning be applied more easily for simple use cases?
- What risks(security, privacy and safety) and ethical considerations are important when using or creating machine learning applications?
If you like your name stated here: This publication is open source. Issues and pull requests are welcome.
All contributors will be added to this list.
So get involved in the discussions and make IT better!
The following people have contributed to this project: [name] [OPTIONAL email] [Optional Organization name ]
When you submit text to which you hold the copyright, you agree to license it under:
- Creative Commons Attribution-ShareAlike 4.0 International License (CC BY-SA 4.0).