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🎰 A curated list of machine learning resources, preferably CoreML

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fantastic-machine-learning

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

Introduction

Models 🚀

  • Awesome-CoreML-Models Largest list of models for Core ML (for iOS 11+)
  • caffe Caffe: a fast open framework for deep learning. http://caffe.berkeleyvision.org/
  • deep-learning-models Keras code and weights files for popular deep learning models.
  • tensorflow models Models built with TensorFlow
  • libSVM A Library for Support Vector Machines
  • scikit-learn Machine Learning in Python
  • xgboost Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Flink and DataFlow
  • Keras-Classification-Models Collection of Keras models used for classification
  • MobileNet-Caffe Caffe Implementation of Google's MobileNets
  • ModelZoo A central GitHub repository for sharing Core ML models
  • StyleArt Style Art library process images using COREML with a set of pre trained machine learning models and convert them to Art style
  • models Models and examples built with TensorFlow

Tools

  • 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

Posts

Repos

  • 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

TensorFlow

Posts

Repos

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

Courses

Machine Learning

Posts

Vision

Natural Language Processing

Metal

GamePlayKit

Courses

Interview

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
  • Torch A SCIENTIFIC COMPUTING FRAMEWORK FOR LUAJIT
  • 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

  • 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.

Statistics

Services

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

Others

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