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I like to explore machine learning, but don't want the to dive into other platforms, like Python or Javascript, to understand some frameworks, or TensorFlow. Luckily, at WWDC 2017, Apple introduces Core ML, Vision, ARKit, which makes working with machine learning so much easier. With all the pre-trained models, we can build great things. It's good to feel the outcome first, then try to explore advanced topics and underlying mechanisms

This will curates things mostly related to Core ML, and Swift. There are related things in other platforms if you want to get some references

Table of contents

Core ML

Models 🚀


  • coremltools coremltools in a python package for creating, examining, and testing models in the .mlmodel format
  • torch2coreml This tool helps convert Torch7 models into Apple CoreML
  • turicreate Turi Create simplifies the development of custom machine learning models.
  • Netron Viewer for neural network and machine learning models
  • onnx-coreml ONNX to CoreML Converter
  • tf-coreml TensorFlow to CoreML Converter
  • tensorwatch Debugging and visualization tool for machine learning and data science



  • Core-ML-Sample A Demo using Core ML Framework
  • UnsplashExplorer-CoreML Core ML demo app with Unsplash API
  • MNIST_DRAW This is a sample project demonstrating the use of Keras (Tensorflow) for the training of a MNIST model for handwriting recognition using CoreML on iOS 11 for inference.
  • CocoaAI The Cocoa Artificial Intelligence Lab 🚀
  • complex-gestures-demo A demonstration of using machine learning to recognize 13 complex gestures in an iOS app
  • Core-ML-Car-Recognition A Car Recognition Framework for CoreML
  • CoreML-in-ARKit Simple project to detect objects and display 3D labels above them in AR. This serves as a basic template for an ARKit project to use CoreML
  • trainer-mac Trains a model, then generates a complete Xcode project that uses it - no code necessary
  • GestureAI-CoreML-iOS Hand-gesture recognition on iOS app using CoreML
  • visual-recognition-coreml Classify images offline using Watson Visual Recognition and Core ML




  • workshops A few exercises for use at events Google IO 2018




Turi Create


Machine Learning

Getting started


Convolution neural network



Create ML

ML Kit


Natural Language Processing





Other ML frameworks

  • TensorSwift A lightweight library to calculate tensors in Swift, which has similar APIs to TensorFlow's
  • Swift-AI The Swift machine learning library.
  • Swift-Brain Artificial intelligence/machine learning data structures and Swift algorithms for future iOS development. bayes theorem, neural networks, and more AI.
  • Bender Easily craft fast Neural Networks on iOS! Use TensorFlow models. Metal under the hood.
  • BrainCore The iOS and OS X neural network framework
  • AIToolbox A toolbox of AI modules written in Swift: Graphs/Trees, Support Vector Machines, Neural Networks, PCA, K-Means, Genetic Algorithms
  • brain Neural networks in JavaScript
  • TensorFlow An open-source software library for Machine Intelligence
  • incubator-predictionio PredictionIO, a machine learning server for developers and ML engineers. Built on Apache Spark, HBase and Spray.
  • Caffe Deep learning framework by BAIR
  • Theano Theano is a Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently
  • CNTK Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit
  • MXNet Lightweight, Portable, Flexible Distributed/Mobile Deep Learning


  • Accelerate-in-Swift Swift example codes for the Accelerate.framework
  • Surge A Swift library that uses the Accelerate framework to provide high-performance functions for matrix math, digital signal processing, and image manipulation.



Text Recognition

Speech Recognition

Speech Synthesizer

  • AVSpeechSynthesizer An object that produces synthesized speech from text utterances and provides controls for monitoring or controlling ongoing speech.

Artificial Intelligence

Google Cloud Platform for Machine Learning


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