Check out my new blog on audio programming at audiodev.blog
14 Sep 2022
— Learn the fundamentals of audio programming by building a fully-featured synth plug-in
1 Sep 2021
— There will be no more updates for my book Core ML Survival Guide.
11 Jan 2021
— Implementation of the SEFR classification algorithm in Swift
25 Nov 2020
— What to do if the predicted bounding boxes are drawn in the wrong place
29 Jun 2020
— A look at what has changed in Apple’s machine learning APIs for iOS and macOS
8 Apr 2020
— Investigating which model architecture makes the best backbone on iPhone
6 Feb 2020
— Because bilinear interpolation does not work the same everywhere
9 Dec 2019
— Make your Core ML models work directly with images instead of multi-arrays
1 Dec 2019
— How to use the new on-device model personalization APIs from Core ML 3
13 Nov 2019
— Using Core ML with Apple’s new reactive programming framework
14 Sep 2019
— How to use the new on-device model personalization APIs from Core ML 3
10 Aug 2019
— How to use the new on-device model personalization APIs from Core ML 3
19 Jul 2019
— How to use the new on-device model personalization APIs from Core ML 3
8 Jun 2019
— What is new in Core ML 3, including all the new neural network layer types
17 Dec 2018
— How to convert SSD to work with Vision’s new object detection API
5 Dec 2018
— Announcing two new books: Machine Learning by Tutorials and the Core ML Survival Guide
16 Aug 2018
— Some examples of how algorithms and data structures are used in real iOS apps
30 Jun 2018
— Finding out how much computation and memory is needed by deep neural networks
9 Jun 2018
— An in-depth look at how fast object detection models are trained
22 Apr 2018
— What is new in MobileNet version 2, and how it stacks up against V1
11 Dec 2017
— How to create your own custom layers with Core ML neural networks
22 Nov 2017
— Machine learning on mobile is currently inference only, but what about training?
2 Sep 2017
— Making a deep convolutional neural network smaller and faster
21 Aug 2017
— Reverse engineering Core ML and the compute kernels it uses under the hood
26 Jul 2017
— What to do when your Core ML model does not output the results you were expecting
23 Jul 2017
— Core ML, Metal Performance Shaders, TensorFlow, or roll your own?
21 Jun 2017
— Showdown between the two new Apple machine learning APIs
14 Jun 2017
— Implementing the MobileNet architecture on iOS. Is it really as fast as its inventors claim?
11 Jun 2017
— Overview and opinions about the new machine learning APIs announced for iOS 11
20 May 2017
— Implementing the YOLO object detection neural network in Metal on iOS
24 Apr 2017
— An open source library that makes it easy to build neural networks with MPSCNN
6 Apr 2017
— Using an LSTM to teach the iPhone how to play the drums
6 Mar 2017
— Learn how to build machine learning models with TensorFlow and put them into your apps
22 Feb 2017
— Comparing matrix multiplication on the GPU against BLAS and fully-connected layers
16 Feb 2017
— The choices to make when you decide to add deep learning to your mobile app
7 Feb 2017
— Comparing the two deep learning APIs Apple introduced in iOS 10
18 Jan 2017
— Learn how OpenGL and Metal work by writing your own 3D renderer from scratch
30 Aug 2016
— Building an image recognition app using Metal
24 Aug 2016
— Using Apple’s new BNNS framework to make a basic neural network
25 Mar 2016
— Take advantage of Swift’s type system to make your programs more expressive and avoid silly mistakes
22 Jul 2015
— A transcript of my talk at the Dutch CocoaHeads meetup in Rotterdam