What is MachineLabs?
MachineLabs is an open source online platform for Machine Learning. We aim to lower the barrier of entry to Machine Learning and embrace knowledge sharing by providing a platform that is accessible, sharable and explorable via the web.
Lowering the barrier of entry to Machine Learning
Machine Learning is a field that still seems rather exclusive to people with academic background (professors, Phd’s, …). It’s often not trivial to follow even beginner guides since the field comes with a heavy focus on mathematical theories. On top of that, setting things up to just get started is also very challenging, especially if one isn’t a data scientist who is familiar with all required tools.
We try to lower the barrier of entry as well as making the tooling scape more pleasant, so more people are able to start learning in this field, by implementing the following features:
- Online Code Editor - People should be able to simply open up a new browser tab and get started. No setup hassle, no prerequisites required. It’s possible to literally copy and paste Machine Learning code and execute it right in the browser.
- Ready to use environments for main ML frameworks - Apart from Tensorflow and Theano, there’s other major libraries like PyTorch or Caffe. MachineLabs provides execution environments for all of these including common libraries needed to perform Machine Learning tasks. Setting up and using a particular environment is as simple as changing one line of configuration code.
- Access to blazingly fast GPU hardware - Training a neural net can take hours, or even several days to finish. That’s why you want to execute your code on super fast GPU optimized machines. MachineLabs will enable you to execute code on blazingly fast GPU accelerated machines.
- Keep track of work - All executions performed stay available so that you can always keep track of your experiments. Each execution offers information about the duration of training, environment and execution status.
- Expose generated assets via API - Outputs and generated assets can be stored on MachineLabs, which can than be downloaded or even requested via a REST API. This enables rich use cases such as building applications on top of trained models.
Embracing knowledge sharing
Our main priority is to make the Machine Learning field accessible to everyone. This not only means lowering the barrier, but also making it easy to share and explore experiments. Coming from the web development landscape, tools like JSFiddle, Plunker and CodePen are the status quo. We want to enable the same for the Machine Learning field by providing features like:
- Sharing public labs - Labs are public by default and can be shared with anyone, anywhere anytime. Whether it’s a freshly trained model or a training that is running in this very moment, so it can be observed by friends.
- Forking labs - Obviously, it should be easy for friends to get started as well. You can take an existing lab and fork it to make a new copy your own. The new lab can now be changed and tweaked to your needs.
- Embedding Labs - MachineLabs provides an embedded editor which can be used to embed labs in websites and blogs. This enables a great experience for readers as they can see the code and their execution from right within the article they are reading.
Why are we raising money?
MachineLabs is an ambitious project that is entirely open source and 100 % bootstrapped. Our main mission is to help the community move forward with Machine Learning. We believe that small, independent, community-focused solutions are very much needed to democratize Machine Learning. Also we'll be moving towards a fully decentralized governance model in which every supporter will gain a stake in the service as well. We'll be most likely using Aragon and/or Harbour to implement that.
Your donation will be used to:
- Build new features for the MachineLabs platform
- Write beautiful, easy digestible docs, guides and tutorials
- Build online Machine Learning training courses
- Enable everyone to use some free GPU hours every month (currently CPU only)
- Provide rich tooling for Machine Learning professionals
- Create visualization support
- Create team features
Why should I back this project?
As a developer it makes sense to back this project to get rewarded with simpler, better tools and online resources for Machine Learning
As a company it makes sense to back this project to:
- Get better tools for your developers to work with
- Help to foster and grow the Machine Learning Community. Your next potential employee may started digging into Machine Learning on MachineLabs.
We've been shipping features in quite a decent pace. You can follow our progress by reading updates in the machinelabs blog.