If you've been following Apple's announcements from the past year, you know that they are heavily invested in machine learning. Ever since they introduced Core ML last year at WWDC 2017, there are tons of apps which have sprung up which harness the power of machine learning. However, one challenge developers always faced was how to create the models? Luckily, Apple solved our question last winter when they announced the acquisition on Turi Create from GraphLab. Turi Create is Apple's tool which can help developers simplify the creation of their own custom models. With Turi Create, you can build your own custom machine learning models.

Create ML is proof that Apple is committed to making it easier for you to use machine learning models in your apps. In this Create ML tutorial, you'll learn how Create ML speeds up the workflow for improving your model by improving your data while also flattening the learning curve by doing it all in the comfort of Xcode and Swift. You don't need to know how to write a compiler to use Swift, and you don't need to be able to write a new ML algorithm to use a classifier. With Create ML, you have no excuse not to get started! You'll start this Create ML tutorial with the spectacular Create ML party trick: You'll build an image classifier in a GUI, using images from the Kaggle Cats and Dogs Dataset. Then you'll compare this with the Turi Create example that uses the same dataset. As you'll see, Turi Create is more manual, but it's also more flexible and not at all mysterious!

Apple last week released Turi Create, an open source package that it says will make it easy for mobile app developers to infuse machine learning into their products with just a few lines of code. "You don't have to be a machine learning expert to add recommendations, object detection, image classification, image similarity, or activity classification to your app," the company says in the GitHub description for Turi Create. From a desktop computer running macOS, Linux, or Windows, Turi Create allows users to apply several machine learning algorithms, including classifiers (like nearest neighbor, SVM, random forests); regression (logistic regression, boosted decision trees); graph analytics (PageCount, K-Core decomposition, triangle count); clustering (K-Means, DBSCAN); and topic models. The software automates the application of the algorithms to a variety of input data, including text, images, audio, video, and sensor data. Users can work with large data sets with a single machine, Apple says.

Turi Create simplifies the development of custom machine learning models. You don't have to be a machine learning expert to add recommendations, object detection, image classification, image similarity or activity classification to your app. It's easy to use the resulting model in an iOS application: For detailed instructions for different varieties of Linux see LINUX_INSTALL.md. For common installation issues see INSTALL_ISSUES.md. We recommend using virtualenv to use, install, or build Turi Create.

Apple's joined other juggernauts of the tech sector by releasing an open source AI framework. Turi Create 4.0, which landed at GitHub recently, is a fruit of its 2016 US$200 million acquisition of Turi. As the GitHub description explains, it targets app developers that want custom machine learning models but don't have the expertise to "add recommendations, object detection, image classification, image similarity or activity classification" to their apps. Completed models are exported to Core ML for use in "iOS, macOS, watchOS, and tvOS apps". Other details noted at the repo include a focus on tasks rather than algorithms; built-in streaming visualisation for data exploration; support for text, images, audio, video, and sensor data; and it can "work with large datasets on a single machine".