Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
awesome-machine-learning
🎰 A curated list of machine learning resources, preferably CoreML
https://github.com/onmyway133/awesome-machine-learning
- Push Hero - pure Swift native macOS application to test push notifications
- PastePal - Pasteboard, note and shortcut manager
- Quick Check - smart todo manager
- Alias - App and file shortcut manager
- My other apps
- Awesome-CoreML-Models
- caffe
- deep-learning-models
- tensorflow models
- libSVM
- scikit-learn
- xgboost
- Keras-Classification-Models
- MobileNet-Caffe
- ModelZoo
- StyleArt
- models
- Core ML Store
- coremltools
- torch2coreml
- turicreate
- Netron
- onnx-coreml
- tf-coreml
- tensorwatch
- Swift Tutorial: Native Machine Learning and Machine Vision in iOS 11
- How to train your own model for CoreML
- Smart Gesture Recognition in iOS 11 with Core ML and TensorFlow
- DIY Prisma app with CoreML
- Using scikit-learn and CoreML to Create a Music Recommendation Engine
- Building Not Hotdog with Turi Create and Core ML — in an afternoon
- Build a Taylor Swift detector with the TensorFlow Object Detection API, ML Engine, and Swift
- Leveraging Machine Learning in iOS For Improved Accessibility
- IBM Watson Services for Core ML Tutorial
- Beginning Machine Learning with Keras & Core ML
- Detecting Whisky brands with Core ML and IBM Watson services
- Detecting Avengers superheroes in your iOS app with IBM Watson and CoreML
- Machine Learning
- Apple Machine Learning Journal
- Introducing Core ML
- Core ML in depth
- Core ML and Vision: Machine Learning in iOS 11 Tutorial
- iOS 11: Machine Learning for everyone
- Everything a Swift Dev Ever Wanted to Know About Machine Learning
- Bringing machine learning to your iOS apps
- Pros and cons of iOS machine learning APIs
- Core ML: Machine Learning for iOS
- Bootstrapping the Machine Learning Training Process
- Detecting Pneumonia in an iOS App with Create ML
- How to fine-tune ResNet in Keras and use it in an iOS App via Core ML
- Five Common Data Quality Gotchas in Machine Learning and How to Detect Them Quickly
- Core-ML-Sample
- UnsplashExplorer-CoreML
- MNIST_DRAW
- CocoaAI
- complex-gestures-demo
- Core-ML-Car-Recognition
- CoreML-in-ARKit
- trainer-mac - no code necessary
- GestureAI-CoreML-iOS - gesture recognition on iOS app using CoreML
- visual-recognition-coreml
- Open Source TensorFlow Models (Google I/O '17)
- Swift for TensorFlow
- Get started with TensorFlow high-level APIs (Google I/O '18)
- Getting started with TensorFlow on iOS
- Introducing TensorFlow.js: Machine Learning in Javascript
- TensorFlow for JavaScript (Google I/O '18)
- Colab
- Use TensorFlow and BNNS to Add Machine Learning to your Mac or iOS App
- workshops
- Machine Learning Crash Course with TensorFlow APIs
- Deep Learning with Python by Francois Chollet
- Learn from ML experts at Google
- Running Keras models on iOS with CoreML
- Keras and Convolutional Neural Networks (CNNs)
- Building Not Hotdog with Turi Create and Core ML — in an afternoon
- Natural Language Processing on iOS with Turi Create
- Machine Learning in iOS: Turi Create and CoreML
- A Guide to Turi Create
- A Thank You note to Towards Data Science
- This is why anyone can learn Machine Learning
- A visual introduction to machine learning
- Machine Learning is Fun!
- 10 Machine Learning Terms Explained in Simple English
- Machine Learning in a Year
- Machine Learning Self-study Resources
- How to Learn Machine Learning
- Getting Started with Machine Learning
- The Non-Technical Guide to Machine Learning & Artificial Intelligence
- Machine Learning: An In-Depth Guide - Overview, Goals, Learning Types, and Algorithms
- A Tour of Machine Learning Algorithms
- Machine Learning for Hackers
- Machine Learning for Developers For absolute beginners and fifth graders
- dive-into-machine-learning - learn
- An introduction to machine learning with scikit-learn
- Building powerful image classification models using very little data
- How HBO’s Silicon Valley built “Not Hotdog” with mobile TensorFlow, Keras & React Nativ
- Hello World - Machine Learning Recipes #1
- An Intuitive Explanation of Convolutional Neural Networks
- A Quick Introduction to Neural Networks
- Machine Learning Algorithm for Flappy Bird using Neural Network and Genetic Algorithm
- Understanding How Machines Learn, Through Prototyping
- Training on the device
- Machine Learning for iOS
- The “hello world” of neural networks
- Convolutional Neural Networks in iOS 10 and macOS
- LearningMachineLearning
- The “hello world” of neural networks
- EmojiIntelligence
- Machine Learning: End-to-end Classification
- Machine Learning Zero to Hero (Google I/O'19)
- CS231n Winter 2016 Lecture 7 Convolutional Neural Networks
- How to build your own Neural Network from scratch in Python
- How Convolutional Neural Networks work
- Fritz Heartbeat
- Introduction to Create ML: How to Train Your Own Machine Learning Model in Xcode 10
- Introducing ML Kit
- Vision - performance image analysis and computer vision techniques to identify faces, detect features, and classify scenes in images and video.
- Blog-Getting-Started-with-Vision
- Swift World: What’s new in iOS 11 — Vision
- NSLinguisticTagger
- Linguistic Tagging
- NSLinguisticTagger on NSHipster
- CoreLinguistics
- SwiftVerbalExpressions
- Metal
- MPSCNNHelloWorld: Simple Digit Detection Convolution Neural Networks (CNN)
- MetalImageRecognition: Performing Image Recognition
- Apple’s deep learning frameworks: BNNS vs. Metal CNN
- Forge
- GamePlayKit
- Project 34: Four in a Row
- GKMinmaxStrategist: What does it take to build a TicTacToe AI?
- GameplayKit Tutorial: Artificial Intelligence
- Gems of GameplayKit
- GameplayKit: Beyond Games
- 6.S191: Introduction to Deep Learning
- Machine Learning
- Introduction - Intro to Machine Learning on Udacity
- Machine Learning & Deep Learning Fundamentals by deeplizard
- 41 Essential Machine Learning Interview Questions
- TensorSwift
- Swift-AI
- Swift-Brain
- Bender
- BrainCore
- AIToolbox - Means, Genetic Algorithms
- brain
- TensorFlow - source software library for Machine Intelligence
- incubator-predictionio
- Caffe
- Torch
- Theano - dimensional arrays efficiently
- CNTK - learning toolkit
- MXNet
- Accelerate-in-Swift
- Surge - performance functions for matrix math, digital signal processing, and image manipulation.
- SigmaSwiftStatistics
- Watson
- wit.ai
- Cloud Machine Learning Engine
- Cloud Vision API
- Amazon Machine Learning
- api.ai - unique, natural language interactions for bots, applications, services, and devices.
- clarifai
- openml
- Lobe
- Comparing Machine Learning (ML) Services from Various Cloud ML Service Providers
- Tesseract OCR Tutorial
- Tesseract-OCR-iOS
- tesseract.js
- Speech
- Using the Speech Recognition API in iOS 10
- Speech Recognition Tutorial for iOS
- CeedVocal
- AVSpeechSynthesizer
- The classic ELIZA chat bot in Swift.
- Introduction to AI Programming for Games
- Machine Learning
- Machine Learning APIs by Example (Google I/O '17)
- Adding Computer Vision to your iOS App
- NotHotdog-Classifier
- How HBO’s Silicon Valley built “Not Hotdog” with mobile TensorFlow, Keras & React Native
Programming Languages
Keywords
machine-learning
16
deep-learning
14
ios
13
coreml
10
swift
9
deep-neural-networks
5
neural-network
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ai
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ios11
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keras
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python
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coremltools
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caffe
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tensorflow
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apple
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cocoa
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vision
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residual-networks
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demo
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core-ml
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machinelearning
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deeplearning
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machine-learning-models
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awesome
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awesome-list
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caffemodel
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coreml-model
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curated-list
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download
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models
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tensorflow-models
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gbdt
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gbm
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