IBM releases Watson Machine Learning for a general audience
Not content with beating humans at quiz shows, IBM is moving forward with its Watson Machine Learning service. Now generally available after a year’s worth of beta testing, WML promises to address the needs of both data scientists and devs.
Machine learning is everywhere these days. Whether it’s recommending your next movie on Netflix or beating Ken Jennings at Jeopardy, ML is here to stay. But how do you get in on this wave?
Interested in training your own little neural network? IBM has just made their new Watson Machine Learning (WML) service generally available this week. I do have to point out that you will need to create an account with Bluemix to start playing around with the service, but there’s a 30 day free trial and it’s pretty fun.
So, what is Watson Machine Learning?
Basically, this is a general machine learning system that is run on IBM’s Bluemix. It’s capable of two different functions of machine learning: training and scoring. Training means that you can use WML to refine an algorithm so that it can ‘learn’ from a datatset. The results of these processes are called models. And scoring is the operation of predicting an outcome using a trained model.
WML is designed to help two different, but complimentary groups: data scientists and developers. The notebook tools is specifically designed for researchers that are looking to learn more about machine learning algorithms. Developers, of course, want to build smart apps that can use predictions made by the machine learning algorithms.
IBM is pretty up front about the fact that there are a lot of open source projects out there that can enable the training of machine learning models. (In fact, we’ve talked about some here and here!) “Data scientists already have a significant set of quality tools they can use in order to perform training operations “, said Armand Ruiz, Lead Product Manager IBM Data Science Experience & Watson ML. “The real challenge facing data scientists is how to operationalize those models.”
According to Ruiz, WML is intended to address questions of deployment, operationalization, and even deriving business value from machine learning models
The new WML has a few cool trciks up its circuity sleeve. Here are a few of the cool things:
- Models as First-Class Entities
- A new user interface called “Model Builder” meant to simplify the creation of Machine Learning models with a more intuitive visual builder experience.
- Notebooks, much like the ones used to train algorithms in Scala, R and Python. “Now it is possible to cover the end-to-end flow without leaving the notebook. Train the model, save the model to a project and deploy that model simply by calling our intuitive APIs!”
- Associate Watson Machine Learning service with Projects: making collaboration between data scientists a snap.
- Collaboration between the App Developer and Data Scientist: App developers will now have access in the Bluemix Dashboard to all of the models created in DSX, as well as the ability to create to easily integrate the ML APIs in to their applications.
So, if you’re interested in trying it out, head on over and give IBM’s Watson Machine Learning a whirl.
Okay, ladies, now let’s get in formation