Before we dive in this week, a minor errata from last weeks issue in which I mentioned that Apple’s new Machine Learning Journal didn’t have an associated RSS feed. Turns out that isn’t the case and the feed *is* actually available here. Thanks to Joe Heck for setting me straight!
Some useful tips from @dilmergames on how to stay sane as an indie developer.
@jemmons looks at the problem of pattern matching and
NSError‘s in Swift. The solution turns out to be much easier than you might have
@zntfdr has discovered a nice little suprise in Xcode 9 Beta 3 onwards… all the Core Graphics geometric data types are now Codable conformant!
@arthurr_here shares his teams experience of using MVVM, Coordinatators and RxSwift to simplify their app architecture.
In this series of articles, @zntfdr provides a gentle introduction to getting started wtih ARKit.
If you’ve looking to brush up on your Core Data concurrency, @MarcoSantaDev has published a nice series of articles that are worth checking out.
@digitalleaves walks through how to get started with the new drag-and-drop APIs in iOS 11.
SwiftCheck is a useful testing library for automatically generating random input data for testing different aspects of an algorithm or data structure.
Following on from the link I included in last weeks issue, @AndrewProjDent has kindly released the source for his ARKit / CoreLocation demo.
When it comes to machine learning on iOS, Core ML is not the only choice. @mhollemans provides a nice summary of the alternatives.
@gregheo searches for a better way of structuring iOS applications by looking at the various ways ViewControllers are used and abused.