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Machine Learning Coming to your Mac OS X

by on March 4, 2015

Here at BigML our mission is to make machine learning easy, beautiful and understandable to everyone. We work hard to make sure that BigML’s REST API and web-based interface offer very intuitive workflows for many types of machine learning tasks. Today, we are proud to announce the BigML native app for Mac OS X, which streamlines machine learning workflows even further. With BigML for Mac OS X you can now generate predictions from your data by just dragging and dropping a file. It’s as simple as that: you do not even need to click once!

There are several key points we’d like to emphasize before giving you more details:

  • Optimized for Cloud Computing: Building machine-learned models is a computationally expensive task because it tends to go through many iterations in an effort to achieve a higher accuracy model. BigML leverages the Cloud’s power, and the native Mac OS X app is capable of handling all related cloud resources necessary.

  • Fast and Cost-free Predictions: Using our Mac OS X client, you can get predictions off of your local data not only faster than using cloud-only alternatives, but as a bonus, it will also cost you a sum total of NOTHING! On top of that, BigML models are white-box, meaning that you can interact with them to better explain why a specific prediction was made.

  • Workflow Templates: Creating Machine Learning models from your data involves some basic steps going from raw data to a final model structure. The app takes care of the workflow and creates all intermediate resources. It will also let you access, modify or reuse those resources to perform other evaluations or optimizations.

Introducing BigML for Mac OS X

BigML for Mac OS X goes to great lengths to ensure that you have all the resources you need in a single, comprehensive view.

BigML for Mac OS X

As seen above, BigML for Mac OS X’s main window has three areas:

  • Project Area: Allows you to create a new project or select an existing one that you can modify.
  • Workflow Area: This section lets you monitor the current state of any on-going operation, select a workflow type and start an operation. The Workflow Area is an “active” area, in that you can drag&drop files or BigML resources on to it to have them processed.
  • Resource Browser: Makes it possible to look up any existing resource (i.e. datasets, models, clusters etc.), inspect their state, and reuse them to start new workflows.

The most important part of BigML’s main window is the Workflow Area. If desired, it is possible to shrink down the Resource Browser area so it does not take any space on your desktop.

Your First Prediction

Creating your first prediction takes only a few seconds. Just locate a data file and drag it on to the central workflow area. After dragging the data file on the workflow area, you will observe how BigML connects to your remote account to create all intermediate resources such as a data source, a dataset, and finally a model, which will be eventually used to generate your predictions. The advantage of BigML for Mac OS X is that you do NOT necessarily need to understand how a model is created and what intermediate steps are taken (or, for that matter, how predictions are computed using the model): The app will take care of that for you.

Wine SaleS Predictions

Eventually, the prediction window will be displayed. There, you will be able to change your model input fields to produce a new prediction. BigML is able to recalculate a prediction “on the fly” while you change the values for the variables shown in the prediction window. It is important to keep in mind that your models are created remotely in the cloud, but they are also replicated locally so that the predictions based on your inputs can be computed locally. That means no network access is required in making new predictions, nor any BigML credits are spent.

Beyond Simple Workflows

BigML for Mac OS X  not only supports tree-based models but also enables cluster analysis (and very soon anomaly detection). Switching from creating models to creating clusters is very easy: you just have to select the corresponding workflow. Now, if you drag the same file as before on BigML main window, you will be able to make new predictions using BigML’s unsupervised clustering algorithms. BigML for Mac OS X is smart enough to automatically update all the related resources and workflows in the background, whenever you make UI selection changes.  This saves you the headache of manually maintaining the proper state of each resource and instead lets you concentrate on getting valuable insights from your data.  In the near future, you won’t only be able to configure your own workflows, but also to personalize them.

BigML Cluster Workflow

Remote and Local Resources

As mentioned above, when you drag a source file over to BigML, a set of resources is created remotely that is also mirrored locally. The Resource Browser allows you to keep an eye on the resources as you create, delete or rename them, and even when you use them to create new predictions, so you do not have to start over every time.

To access the Resource Browser, just click the down-arrow in the bottom-right corner of the BigML main window. You can select a specific resource type in the resource browser to see what resources of that type you have created. If you right-click on a resource, you will access a pop-up menu offering a few options such as renaming the resource, deleting it from the server etc. Finally, you can drag any resource in the workflow area, it will be used as a starting point to create a new model or cluster. This gives you an alternate way to create a prediction.

How Can I Get It?

We are about to kick off the BigML for Mac OS X private beta. If you are interested, drop a note to bigmlx@bigml.com and we’ll include you in our beta testers list as soon as the private beta starts.

BigML for Mac OS X is now officially available. You can download and use it freely. Please, send your feedback to bigmlx@bigml.com, we are eager to hear you!

A Note for Developers

BigML for Mac OS X has been implemented using BigML iOS bindings. That is, just plain vanilla BigML’s REST API.  So if you are in hacking mood, imagine how easy powering your Mac OS X application with machine learning can be.

What’s Next? Tell Me about the ‘Big Picture’ Already

You bet! It is our conviction that as soon as 5 years from now, we will be living in a world where interfacing with machine-learned models will be as natural and seamless for a business analyst as it is for any of us to interface with an iPhone today.  If we succeed, it’ll be all as natural (and taken for granted) as the air around us. BigML’s native Mac OS X client may be one small step in this direction, but make no mistake about it…in hindsight, it may also prove to be one giant step for 21st century business in the not so distant future.  Will you be there with us?  Or will you still be staring at an Excel spreadsheet? The choice is yours!

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