Explore Machine Learning Models Without Writing Code or Installing Packages
Up and Deployed : ml4everyone.com
Machine Learning | Artificial Intelligence | Deep Learning — they ARE the next big thing, I know it, we all know it. Then why wait? What keeps us from grabbing the opportunity when its right in front of us? Maybe because taking a step off from daily chores and doing something new requires a bit of effort.
Back in the days when I started to explore machine learning and its applications, a significant portion of my time got wasted in guess what? — figuring out and researching 1. the language to use, 2. framework to choose, 3. installing (installing it the right way) and setting up a development environment. After all the drama, I get to start actual development.
Machine Learning | Artificial Intelligence | Deep Learning — they ARE the next big thing, I know it, we all know it.
Then comes the idea of building a cloud based application where anyone can start harnessing the power of machine learning and it will take care of the rest. Of course there are plenty of service available — one is BigML, but for my own practice and satisfaction, I started to develop the idea.
It became my dream project overnight; An independent web application where one can learn and test Machine Learning models through APIs. No more coding expertise, installation headaches, compatibility issues, need for a powerful rig. Even Postman could run it.
And the best part is; it is open source, the complete application can be forked from Github.
This is an active project under development. More complex models coming soon …
Right now, as bare essentials to any ML System, there are two models deployed: K-Nearest Neighbour Classifier and Linear Regression. There is plenty of room to play around these. I am learning Google’s TensorFlow in the meantime which will greatly help. But for the application, to keep things simple, scikit-learn framework has been chosen. It is an awesome library in Python for learning.
I am looking forward for like minded folks, just like me who are willing to help or contribute to the project. The project is hosted on Github and I would be glad to accept some pull requests. :)