Last Update: January 12, 2018.
Curated list of resources for iOS developers in following topics:
Most of the de-facto standard tools in AI-related domains are written in iOS-unfriendly languages (Python/Java/R/Matlab) so finding something appropriate for your iOS application may be a challenging task.
Resources are sorted alphabetically or randomly. The order doesn't reflect my personal preferences or anything else. Some of the resources are awesome, some are great, some are fun, and some can serve as an inspiration.
Pull-requests are welcome here.
Currently CoreML is compatible (partially) with the following machine learning packages via coremltools python package:
Third-party converters to CoreML format are also available for some models from:
Core ML currently doesn't support training models, but still, you can replace model by downloading a new one from a server in runtime. Here is a demo of how to do it. It uses generator part of MNIST GAN as Core ML model.
||C++||GNU LGPL 2.1||GitHub||Cocoa Pods|
|lbimproved||k-nearest neighbors and Dynamic Time Warping||C++||Apache 2.0||GitHub|
||Swift||Apache 2.0||GitHub||Swift Package Manager|
||C++||3-clause BSD||GitHub||Cocoa Pods|
||C++||GNU LGPL||GitHub||Cocoa Pods|
||Objective-C||GNU GPL 3.0||GitHub|
Kalvar Lin's libraries
Multilayer perceptron implementations:
These libraries doesn't support training, so you need to pre-train models in some ML framework.
OpenCL for iOS - just a test.
Exploring GPGPU on iOS.
GPU-accelerated video processing for Mac and iOS. Article.
Concurrency and OpenGL ES - Apple programming guide.
OpenCV on iOS GPU usage - SO discussion.
Please note that in this section, I'm not trying to collect another list of ALL machine learning study resources, but only composing a list of things that I found useful.