├── .gitignore ├── CreateML.playground ├── Pages │ ├── Images CreateML.xcplaygroundpage │ │ └── Contents.swift │ ├── Images CreateMLUI.xcplaygroundpage │ │ └── Contents.swift │ ├── Table of contents.xcplaygroundpage │ │ └── Contents.swift │ ├── Tabular Data.xcplaygroundpage │ │ └── Contents.swift │ └── Text.xcplaygroundpage │ │ └── Contents.swift ├── Resources │ └── Data │ │ ├── image │ │ ├── test │ │ │ ├── fast food │ │ │ │ ├── 1430762923_150428151601papitas1624x351thinkstock.jpg │ │ │ │ ├── 18COOKING-MCBITTYBEANBURGERS2-articleLarge.jpg │ │ │ │ ├── 28988529927_7525ba8a9a_b.jpg │ │ │ │ ├── 59669a520976db34008b4cd7-750-563.jpg │ │ │ │ ├── Subway.jpg │ │ │ │ ├── These-burgers-are-so-delicious-and-full-of-flavor-you-cant-get-enough-.jpg │ │ │ │ ├── b43f786c4d6e31025295c16023cded99.jpg │ │ │ │ ├── baklava411.jpg │ │ │ │ ├── best+burgers.jpg │ │ │ │ ├── best-black-bean-burgers-2.jpg │ │ │ │ ├── burger-fijpg-57e7e5907630c2ad.jpg │ │ │ │ ├── butter-burgers-recipe-8-of-8.jpg │ │ │ │ ├── candy-fast-food-baklava-honey-price-47541.jpg │ │ │ │ ├── ffac757fc64d1e414422bf204f1a4f87.jpg │ │ │ │ ├── gourmet-burger-1024x666.jpg │ │ │ │ ├── jollibee.0.png │ │ │ │ └── z16728381IE,fast-food.jpg │ │ │ └── healthy │ │ │ │ ├── 1_vRO0Q2T-heSGJfTYMexDmg.jpeg │ │ │ │ ├── 470979997.jpg │ │ │ │ ├── 9509951988_ef2fc281d4_h.jpg │ │ │ │ ├── ABUNDANCE-Green-Salad-with-Savory-Tahini-Dressing-30-min-full-of-fiber-nutrients-vegan-glutenfree-salad-plantbased-healthy-recipe-minimalistbaker-500.jpg │ │ │ │ ├── Chickpea-Salad-spendwithpennies.com-23.jpg │ │ │ │ ├── Gezonde-lunch.jpg │ │ │ │ ├── Greenest-Green-Salad-LEDE.jpg │ │ │ │ ├── Screen%20Shot%202018-05-22%20at%202.58.39%20PM.png │ │ │ │ ├── avocado-salad-1524672116.png │ │ │ │ ├── cl_digi_58.jpg │ │ │ │ ├── d03895443badf2e5f0322a213d83ea45.jpg │ │ │ │ ├── exps6498_MRR133247D07_30_5b_WEB-2.jpg │ │ │ │ ├── getimage.jpeg │ │ │ │ ├── salad-2150548_1280.jpg │ │ │ │ ├── salad-861x576.jpg │ │ │ │ ├── salada-fit-saladex.jpg │ │ │ │ ├── strawberry-chicken-salad-with-pecans.jpg │ │ │ │ ├── tkphoto_0405180056.jpg │ │ │ │ └── what-is-clean-eating-everything-you-need-to-know-about-the-healthy-food-trend-136413844057003901-170120162318.jpg │ │ └── train │ │ │ ├── fast food │ │ │ ├── 0044d20df995abde.jpg │ │ │ ├── 0049005b0f5eeb57.jpg │ │ │ ├── 004903710bc67e93.jpg │ │ │ ├── 0081b743c9ebc7b5.jpg │ │ │ ├── 027c59ab4d1c49fa.jpg │ │ │ ├── 04b58113048012af.jpg │ │ │ ├── 052b27e426e81601.jpg │ │ │ ├── 06173f4c2ce12033.jpg │ │ │ ├── 0626212e34854ecb.jpg │ │ │ ├── 063e678d07b06a91.jpg │ │ │ ├── 066fe03ebf613118.jpg │ │ │ ├── 072d817e5a08b259.jpg │ │ │ ├── 0a56ec8ec6766b3d.jpg │ │ │ ├── 15ac6b22cd6ee832.jpg │ │ │ ├── 160413083833_1_540x360.jpg │ │ │ ├── 160826-F-HU835-038.JPG │ │ │ ├── 166ad6a12c8f81f9.jpg │ │ │ ├── 1bdb433f953df5fe.jpg │ │ │ ├── 1cf008a88d00b921.jpg │ │ │ ├── 1de50e6fe5bd3dd1.jpg │ │ │ ├── 2009fc2f4090849b.jpg │ │ │ ├── 2103a9584a9dff13.jpg │ │ │ ├── 22e3af669dd68c15.jpg │ │ │ ├── 235f9b49aeff2d32.jpg │ │ │ ├── 291f52f73bfed401.jpg │ │ │ ├── 2ad3395ed1d7ba16.jpg │ │ │ ├── 2f4d7fa413962ae5.jpg │ │ │ ├── 2f941ea03ab0c6d8.jpg │ │ │ ├── 2f99ffb3b1f7fbba.jpg │ │ │ ├── 32d3bb5672b4fab3.jpg │ │ │ ├── 3307ad7b6af6ac5b.jpg │ │ │ ├── 33526f2e5af21ab8.jpg │ │ │ ├── 33e3cc014591c27c.jpg │ │ │ ├── 35a01f5384a6df4d.jpg │ │ │ ├── 39f6296778264878.jpg │ │ │ ├── 3e66e184fc661667.jpg │ │ │ ├── 3ede185b7637b313.jpg │ │ │ ├── 3fd8dcd1f11954dd.jpg │ │ │ ├── 41fb0cd944744b8d.jpg │ │ │ ├── 4360eae581327bea.jpg │ │ │ ├── 45119eddf20dabf8.jpg │ │ │ ├── 5742bf39a45f0.jpg │ │ │ ├── 5a71007359d432823c8b47dc-750-500.jpg │ │ │ ├── 89fe591d13a8f002f09acee4eecbd99040f6d64e.jpeg │ │ │ ├── Chicken_Nuggets__opener_22.0.jpg │ │ │ ├── FAST-FOOD.jpg │ │ │ ├── Fast_food_meal.jpg │ │ │ ├── Hamburger_Bun_small_ChN5za2.jpg │ │ │ ├── SSI_20140624102438_V.jpg │ │ │ ├── donut-2758808_1280.jpg │ │ │ ├── fast-food-secrets.jpg │ │ │ ├── fastfood-1.jpg │ │ │ ├── french-fries-508292_1280.jpg │ │ │ ├── fried-chicken-690039_1280.jpg │ │ │ ├── fried_foods_570.jpg │ │ │ ├── gorengan.jpg │ │ │ ├── imagenes-de-comida-1.jpg │ │ │ ├── rectass.jpg │ │ │ └── trade-new-photos-sandwiches-47442.jpg │ │ │ └── healthy │ │ │ ├── 000fb70c8e06a57c.jpg │ │ │ ├── 00c6c293d3218868.jpg │ │ │ ├── 00e9354a425c217b.jpg │ │ │ ├── 015a6a543a85603b.jpg │ │ │ ├── 02033a9b801254a2.jpg │ │ │ ├── 02442c69b7901224.jpg │ │ │ ├── 0272a647cc0d98ed.jpg │ │ │ ├── 032fea0078524ac9.jpg │ │ │ ├── 0554e3729b683aef.jpg │ │ │ ├── 06c1b1b0bece3417.jpg │ │ │ ├── 07ab32a6690474e5.jpg │ │ │ ├── 0896f10d95e3664d.jpg │ │ │ ├── 08dabf1302bb5aab.jpg │ │ │ ├── 0a550114df716168.jpg │ │ │ ├── 0b28e8c46c87106f.jpg │ │ │ ├── 0b4363cb993d1198.jpg │ │ │ ├── 0b540b1e950ff60f.jpg │ │ │ ├── 0b5a27ce480dea34.jpg │ │ │ ├── 0b90cc8776bad898.jpg │ │ │ ├── 0d5580c17ccfc22b.jpg │ │ │ ├── 0dbb3ae6c87928fa.jpg │ │ │ ├── 0f18db5ae9e378c0.jpg │ │ │ ├── 0fd5bdbb38b4814e.jpg │ │ │ ├── 1728e888d7bb37ed.jpg │ │ │ ├── 187e1876e5a30b91.jpg │ │ │ ├── 18aeee69c0256250.jpg │ │ │ ├── 18b848eb1f5a09d7.jpg │ │ │ ├── 1a61c267c04a8413.jpg │ │ │ ├── 1bf3f8ce434ae502.jpg │ │ │ ├── 1c8ef8894f4480f6.jpg │ │ │ ├── 1e707f5493aaca74.jpg │ │ │ ├── 1e74d12a0a9afff1.jpg │ │ │ ├── 2097bdb2f8ef7860.jpg │ │ │ ├── 2223c973784fce41.jpg │ │ │ ├── 23eaeac7441beea2.jpg │ │ │ ├── 241e754e31686daa.jpg │ │ │ ├── 259a3b00e26f57bf.jpg │ │ │ ├── 26bfae4d751521ac.jpg │ │ │ ├── 26c7c80540f5980b.jpg │ │ │ ├── 275df8ed757abc9c.jpg │ │ │ ├── 28fbeece2dae82ed.jpg │ │ │ ├── 2a7bfb8c14334a2e.jpg │ │ │ ├── 2ad03070c5900aac.jpg │ │ │ ├── 2b4ff35008b3521c.jpg │ │ │ ├── 2e338198044a9806.jpg │ │ │ ├── 2fc2e370b208e71d.jpg │ │ │ ├── 30c4f52ffe41bf51.jpg │ │ │ ├── 31e76d4bc58fb708.jpg │ │ │ ├── 32e74b1950434612.jpg │ │ │ ├── 32f7cbba4c9d0b3a.jpg │ │ │ ├── 336be5ef3734c92d.jpg │ │ │ ├── 37e6511595c75a7c.jpg │ │ │ ├── 38dc0b5c761f6ff3.jpg │ │ │ ├── 3a200b6e92c53d72.jpg │ │ │ ├── 3ba335d1d93957de.jpg │ │ │ ├── 3bf31a8e439da3f3.jpg │ │ │ ├── 3cb0d16293f49e7e.jpg │ │ │ ├── 3d3fd58c34b52a5f.jpg │ │ │ ├── 3ded13df1ee33f34.jpg │ │ │ ├── 3f2bb5676aa89475.jpg │ │ │ ├── 3fac95571b49b06e.jpg │ │ │ ├── 3fb1728775535422.jpg │ │ │ └── 43f64d360fd0e47c.jpg │ │ ├── table │ │ └── data.json │ │ └── text │ │ ├── test │ │ └── data.json │ │ └── train │ │ └── data.json └── contents.xcplayground └── README.md /.gitignore: -------------------------------------------------------------------------------- 1 | .DS_Store 2 | .Trashes 3 | .localized 4 | 5 | build 6 | .build 7 | xcuserdata 8 | DerivedData 9 | 10 | *.mode1v3 11 | *.mode2v3 12 | *.perspectivev3 13 | *.pbxuser 14 | *.xccheckout 15 | *.xcuserstate 16 | *.xcscmblueprint 17 | *.moved-aside 18 | *.hmap 19 | *.o 20 | *.hmap 21 | *.ipa 22 | *.dSYM.zip 23 | 24 | timeline.xctimeline 25 | playground.xcworkspace 26 | 27 | .idea 28 | *.iml 29 | 30 | Pods 31 | Carthage 32 | Packages 33 | 34 | fastlane/report.xml 35 | fastlane/Preview.html 36 | fastlane/screenshots 37 | fastlane/test_output 38 | 39 | .env -------------------------------------------------------------------------------- /CreateML.playground/Pages/Images CreateML.xcplaygroundpage/Contents.swift: -------------------------------------------------------------------------------- 1 | /*: 2 | That's an example of a bit more advanced way to create a model, in comparison to CreateMLUI method. 3 | */ 4 | 5 | import CreateML 6 | import Foundation 7 | 8 | // Initializing the properly labeled training data from Resources folder. 9 | let trainingDataPath = Bundle.main.path(forResource: "train", ofType: nil, inDirectory: "Data/image")! 10 | let trainingData = MLImageClassifier.DataSource.labeledDirectories(at: URL(fileURLWithPath: trainingDataPath)) 11 | 12 | // Initializing the classifier with a training data. 13 | let classifier = try! MLImageClassifier(trainingData: trainingData) 14 | 15 | // Evaluating training & validation accuracies. 16 | let trainingAccuracy = (1.0 - classifier.trainingMetrics.classificationError) * 100 17 | let validationAccuracy = (1.0 - classifier.validationMetrics.classificationError) * 100 18 | 19 | // Initializing the properly labeled testing data from Resources folder. 20 | let testingDataPath = Bundle.main.path(forResource: "test", ofType: nil, inDirectory: "Data/image")! 21 | let testingData = MLImageClassifier.DataSource.labeledDirectories(at: URL(fileURLWithPath: testingDataPath)) 22 | 23 | // Counting the testing evaluation. 24 | let evaluationMetrics = classifier.evaluation(on: testingData) 25 | let evaluationAccuracy = (1.0 - evaluationMetrics.classificationError) * 100 26 | 27 | // Confusion matrix in order to see which labels were classified wrongly. 28 | let confusionMatrix = evaluationMetrics.confusion 29 | print("Confusion matrix: \(confusionMatrix)") 30 | 31 | // Metadata for saving the model. 32 | let metadata = MLModelMetadata(author: "Author", 33 | shortDescription: "A model trained to classify healthy and fast food lunch", 34 | version: "1.0") 35 | 36 | // Saving the model. Remember to update the path. 37 | try classifier.write(to: URL(fileURLWithPath: "Path where you would like to save the model"), 38 | metadata: metadata) 39 | 40 | /*: 41 | [Table of contents](Table%20of%20contents) • [Previous page](@previous) • [Next page](@next) 42 | */ 43 | -------------------------------------------------------------------------------- /CreateML.playground/Pages/Images CreateMLUI.xcplaygroundpage/Contents.swift: -------------------------------------------------------------------------------- 1 | /*: 2 | Run the playground and drag properly labeled training data. After training do the same with testing data and save a model. The easiest way to create an ImageClassifier! 🎉 3 | */ 4 | import CreateMLUI 5 | 6 | let builder = MLImageClassifierBuilder() 7 | builder.showInLiveView() 8 | 9 | /*: 10 | [Table of contents](Table%20of%20contents) • [Next page](@next) 11 | */ 12 | -------------------------------------------------------------------------------- /CreateML.playground/Pages/Table of contents.xcplaygroundpage/Contents.swift: -------------------------------------------------------------------------------- 1 | /*: 2 | # CreateML Research Playground 3 | 4 | By [Anna-Mariia Shkarlinska @Netguru](https://github.com/anyashka) • November 2018\ 5 | [Source on GitHub](https://github.com/netguru/CreateML-Research)\ 6 | [Blog post](https://www.netguru.co/codestories/createml-start-your-adventure-in-machine-learning-with-swift) 7 | 8 | ## Contents 9 | 10 | 1. [Images with CreateMLUI](Images%20CreateMLUI) 11 | 1. [Images with CreateML](Images%20CreateML) 12 | 1. [Text](Text) 13 | 1. [Tabular Data](Tabular%20Data) 14 | 15 | ## Requirements 16 | 17 | - macOS 10.14+ 18 | - Xcode 10+ 19 | 20 | ## Note 21 | 22 | This Playground contains the easy ways to start your journey with CreateML and is a part of the CreateML blog post on Netguru blog. The demo app [`Healthy Luncher`](https://github.com/netguru/HealthyLuncher-Demo) was also created for the purpose of this research. With its help it is possible to check out how the models work. 23 | */ 24 | /*: 25 | [Next page](@next) 26 | */ 27 | -------------------------------------------------------------------------------- /CreateML.playground/Pages/Tabular Data.xcplaygroundpage/Contents.swift: -------------------------------------------------------------------------------- 1 | /*: 2 | Tabular data classification. 3 | */ 4 | import CreateML 5 | import Foundation 6 | 7 | // Initializing the data from Resources folder. 8 | let dataPath = Bundle.main.path(forResource: "data", ofType: "json", inDirectory: "Data/table")! 9 | let dataTable = try! MLDataTable(contentsOf: URL(fileURLWithPath: dataPath)) 10 | 11 | // Spliting the data into training and testing ones. 12 | let (trainingData, testingData) = dataTable.randomSplit(by: 0.8, seed: 5) 13 | 14 | // Initializing the classifier with a training data. 15 | let classifier = try! MLClassifier(trainingData: trainingData, targetColumn: "type") 16 | 17 | // The alternative way of initializing manually a concrete classifier. 18 | /* 19 | var modelParameters = MLBoostedTreeClassifier.ModelParameters() 20 | modelParameters.maxIterations = 20 21 | let classifier = try! MLBoostedTreeClassifier(trainingData: trainingData, targetColumn: "type", featureColumns: nil, parameters: modelParameters) 22 | */ 23 | 24 | // Evaluating training & validation accuracies. 25 | let trainingAccuracy = (1.0 - classifier.trainingMetrics.classificationError) * 100 26 | let validationAccuracy = (1.0 - classifier.validationMetrics.classificationError) * 100 27 | 28 | // Initializing the properly labeled testing data from Resources folder. 29 | let evaluationMetrics = classifier.evaluation(on: testingData) 30 | let evaluationAccuracy = (1.0 - evaluationMetrics.classificationError) * 100 31 | 32 | // Confusion matrix in order to see which labels were classified wrongly. 33 | let confusionMatrix = evaluationMetrics.confusion 34 | print("Confusion matrix: \(confusionMatrix)") 35 | 36 | // Metadata for saving the model. 37 | let metadata = MLModelMetadata(author: "Author", 38 | shortDescription: "A model trained to classify healthy and fast food lunch", 39 | version: "1.0") 40 | // Saving the model. Remember to update the path. 41 | try classifier.write(to: URL(fileURLWithPath: "Path where you would like to save the model"), 42 | metadata: metadata) 43 | /*: 44 | [Table of contents](Table%20of%20contents) • [Previous page](@previous) 45 | */ 46 | -------------------------------------------------------------------------------- /CreateML.playground/Pages/Text.xcplaygroundpage/Contents.swift: -------------------------------------------------------------------------------- 1 | /*: 2 | Text classification. 3 | */ 4 | import CreateML 5 | import Foundation 6 | 7 | // Initializing the training data from Resources folder. 8 | let trainingDataPath = Bundle.main.path(forResource: "data", ofType: "json", inDirectory: "Data/text/train")! 9 | let trainingData = try! MLDataTable(contentsOf: URL(fileURLWithPath: trainingDataPath)) 10 | 11 | // Initializing the classifier with a training data. 12 | let classifier = try! MLTextClassifier(trainingData: trainingData, textColumn: "text", labelColumn: "type") 13 | 14 | // Evaluating training & validation accuracies. 15 | let trainingAccuracy = (1.0 - classifier.trainingMetrics.classificationError) * 100 16 | let validationAccuracy = (1.0 - classifier.validationMetrics.classificationError) * 100 17 | 18 | // Initializing the properly labeled testing data from Resources folder. 19 | let testingDataPath = Bundle.main.path(forResource: "data", ofType: "json", inDirectory: "Data/text/test")! 20 | let testingData = try! MLDataTable(contentsOf: URL(fileURLWithPath:testingDataPath)) 21 | 22 | // Counting the testing evaluation. 23 | let evaluationMetrics = classifier.evaluation(on: testingData) 24 | let evaluationAccuracy = (1.0 - evaluationMetrics.classificationError) * 100 25 | 26 | // Confusion matrix in order to see which labels were classified wrongly. 27 | let confusionMatrix = evaluationMetrics.confusion 28 | print("Confusion matrix: \(confusionMatrix)") 29 | 30 | // Metadata for saving the model. 31 | let metadata = MLModelMetadata(author: "Author", 32 | shortDescription: "A model trained to classify healthy and fast food lunch", 33 | version: "1.0") 34 | 35 | // Saving the model. Remember to update the path. 36 | try classifier.write(to: URL(fileURLWithPath: "Path where you would like to save the model"), 37 | metadata: metadata) 38 | 39 | /*: 40 | [Table of contents](Table%20of%20contents) • [Previous page](@previous) • [Next page](@next) 41 | */ 42 | -------------------------------------------------------------------------------- /CreateML.playground/Resources/Data/image/test/fast food/1430762923_150428151601papitas1624x351thinkstock.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/netguru/CreateML-Research/b1fb298949ffd9542c36b95e909f1aacd48b65df/CreateML.playground/Resources/Data/image/test/fast food/1430762923_150428151601papitas1624x351thinkstock.jpg -------------------------------------------------------------------------------- /CreateML.playground/Resources/Data/image/test/fast food/18COOKING-MCBITTYBEANBURGERS2-articleLarge.jpg: 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https://raw.githubusercontent.com/netguru/CreateML-Research/b1fb298949ffd9542c36b95e909f1aacd48b65df/CreateML.playground/Resources/Data/image/train/healthy/43f64d360fd0e47c.jpg -------------------------------------------------------------------------------- /CreateML.playground/Resources/Data/table/data.json: -------------------------------------------------------------------------------- 1 | [ 2 | { 3 | "name": "Snickers", 4 | "company": "Mars", 5 | "price": 2, 6 | "type": "fast food" 7 | }, { 8 | "name": "Burger", 9 | "company": "McDonalds", 10 | "price": 2, 11 | "type": "fast food" 12 | }, { 13 | "name": "Fries", 14 | "company": "Burger King", 15 | "price": 1, 16 | "type": "fast food" 17 | }, { 18 | "name": "Fried chicken bucket", 19 | "company": "KFC", 20 | "price": 3, 21 | "type": "fast food" 22 | }, { 23 | "name": "Pizza", 24 | "company": "Pizza Hut", 25 | "price": 4, 26 | "type": "fast food" 27 | }, { 28 | "name": "Vegetable stew", 29 | "company": "EAT", 30 | "price": 5, 31 | "type": "healthy" 32 | }, { 33 | "name": "Curry with boiled fish", 34 | "company": "Whole Foods", 35 | "price": 5, 36 | "type": "healthy" 37 | }, { 38 | "name": "Salad", 39 | "company": "Fresh", 40 | "price": 6, 41 | "type": "healthy" 42 | }, { 43 | "name": "Grilled tuna", 44 | "company": "Natural", 45 | "price": 7, 46 | "type": "healthy" 47 | }, { 48 | "name": "Fruit salad", 49 | "company": "Healhy", 50 | "price": 8, 51 | "type": "healthy" 52 | } 53 | ] -------------------------------------------------------------------------------- /CreateML.playground/Resources/Data/text/test/data.json: -------------------------------------------------------------------------------- 1 | 2 | [ 3 | { 4 | "text": "fat", 5 | "type": "fast food" 6 | }, { 7 | "text": "hamburger", 8 | "type": "fast food" 9 | }, { 10 | "text": "sweets", 11 | "type": "fast food" 12 | }, { 13 | "text": "sugar coated nuts", 14 | "type": "fast food" 15 | }, { 16 | "text": "burger with fries", 17 | "type": "fast food" 18 | }, { 19 | "text": "oily potatoes", 20 | "type": "fast food" 21 | }, { 22 | "text": "deep fried fish", 23 | "type": "fast food" 24 | }, { 25 | "text": "fat meat", 26 | "type": "fast food" 27 | }, { 28 | "text": "avocado salad", 29 | "type": "healthy" 30 | }, { 31 | "text": "tuna wrap", 32 | "type": "healthy" 33 | }, { 34 | "text": "nutritious sandwich", 35 | "type": "healthy" 36 | }, { 37 | "text": "fresh vegetables", 38 | "type": "healthy" 39 | }, { 40 | "text": "grilled fish", 41 | "type": "healthy" 42 | }, { 43 | "text": "boiled potatoes", 44 | "type": "healthy" 45 | }, { 46 | "text": "fruit salad", 47 | "type": "healthy" 48 | }, { 49 | "text": "homecooked soup", 50 | "type": "healthy" 51 | } 52 | ] -------------------------------------------------------------------------------- /CreateML.playground/Resources/Data/text/train/data.json: -------------------------------------------------------------------------------- 1 | 2 | [ 3 | { 4 | "text": "burger", 5 | "type": "fast food" 6 | }, { 7 | "text": "fried", 8 | "type": "fast food" 9 | }, { 10 | "text": "mcdonalds", 11 | "type": "fast food" 12 | }, { 13 | "text": "oily", 14 | "type": "fast food" 15 | }, { 16 | "text": "crispy", 17 | "type": "fast food" 18 | }, { 19 | "text": "fat", 20 | "type": "fast food" 21 | }, { 22 | "text": "hamburger", 23 | "type": "fast food" 24 | }, { 25 | "text": "pizza", 26 | "type": "fast food" 27 | }, { 28 | "text": "bagel", 29 | "type": "fast food" 30 | }, { 31 | "text": "bread", 32 | "type": "fast food" 33 | }, { 34 | "text": "waffle", 35 | "type": "fast food" 36 | }, { 37 | "text": "unhealthy", 38 | "type": "fast food" 39 | }, { 40 | "text": "microwave", 41 | "type": "fast food" 42 | }, { 43 | "text": "cookies", 44 | "type": "fast food" 45 | }, { 46 | "text": "sausage", 47 | "type": "fast food" 48 | }, { 49 | "text": "donut", 50 | "type": "fast food" 51 | }, { 52 | "text": "junk", 53 | "type": "fast food" 54 | }, { 55 | "text": "sweets", 56 | "type": "fast food" 57 | }, { 58 | "text": "processed", 59 | "type": "fast food" 60 | }, { 61 | "text": "sugar", 62 | "type": "fast food" 63 | }, { 64 | "text": "sugar coated nuts", 65 | "type": "fast food" 66 | }, { 67 | "text": "tempura", 68 | "type": "fast food" 69 | }, { 70 | "text": "noodle", 71 | "type": "fast food" 72 | }, { 73 | "text": "kebab", 74 | "type": "fast food" 75 | }, { 76 | "text": "street-food", 77 | "type": "fast food" 78 | }, { 79 | "text": "bacon", 80 | "type": "fast food" 81 | }, { 82 | "text": "chips", 83 | "type": "fast food" 84 | }, { 85 | "text": "baguette", 86 | "type": "fast food" 87 | }, { 88 | "text": "muffin", 89 | "type": "fast food" 90 | }, { 91 | "text": "croisant", 92 | "type": "fast food" 93 | }, { 94 | "text": "pancake", 95 | "type": "fast food" 96 | }, { 97 | "text": "tuna wrap", 98 | "type": "healthy" 99 | }, { 100 | "text": "macrobiotics", 101 | "type": "healthy" 102 | }, { 103 | "text": "wholesome", 104 | "type": "healthy" 105 | }, { 106 | "text": "homecooked", 107 | "type": "healthy" 108 | }, { 109 | "text": "natural", 110 | "type": "healthy" 111 | }, { 112 | "text": "soup", 113 | "type": "healthy" 114 | }, { 115 | "text": "grilled", 116 | "type": "healthy" 117 | }, { 118 | "text": "nourishment", 119 | "type": "healthy" 120 | }, { 121 | "text": "vitamins", 122 | "type": "healthy" 123 | }, { 124 | "text": "nutritious", 125 | "type": "healthy" 126 | }, { 127 | "text": "fresh", 128 | "type": "healthy" 129 | }, { 130 | "text": "wholemeal", 131 | "type": "healthy" 132 | }, { 133 | "text": "wholegrain", 134 | "type": "healthy" 135 | }, { 136 | "text": "vegan", 137 | "type": "healthy" 138 | }, { 139 | "text": "protein", 140 | "type": "healthy" 141 | }, { 142 | "text": "spinach", 143 | "type": "healthy" 144 | }, { 145 | "text": "beans", 146 | "type": "healthy" 147 | }, { 148 | "text": "hummus", 149 | "type": "healthy" 150 | }, { 151 | "text": "lettuce", 152 | "type": "healthy" 153 | }, { 154 | "text": "homemade", 155 | "type": "healthy" 156 | }, { 157 | "text": "avocado", 158 | "type": "healthy" 159 | }, { 160 | "text": "smoothie", 161 | "type": "healthy" 162 | }, { 163 | "text": "banana", 164 | "type": "healthy" 165 | }, { 166 | "text": "apple", 167 | "type": "healthy" 168 | }, { 169 | "text": "fruits", 170 | "type": "healthy" 171 | }, { 172 | "text": "vegetables", 173 | "type": "healthy" 174 | }, { 175 | "text": "raw", 176 | "type": "healthy" 177 | }, { 178 | "text": "boiled", 179 | "type": "healthy" 180 | }, { 181 | "text": "fish", 182 | "type": "healthy" 183 | }, { 184 | "text": "salad", 185 | "type": "healthy" 186 | }, { 187 | "text": "peanut butter", 188 | "type": "healthy" 189 | }, { 190 | "text": "kombucha", 191 | "type": "healthy" 192 | }, { 193 | "text": "kale", 194 | "type": "healthy" 195 | }, { 196 | "text": "basil", 197 | "type": "healthy" 198 | }, { 199 | "text": "almond milk", 200 | "type": "healthy" 201 | } 202 | ] -------------------------------------------------------------------------------- /CreateML.playground/contents.xcplayground: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # CreateML-Research 2 | The playground that contains the easy ways to start your journey with **CreateML** and is a part of the [CreateML blog post](https://www.netguru.co/codestories/createml-start-your-adventure-in-machine-learning-with-swift). The demo app [Healthy Luncher](https://github.com/netguru/HealthyLuncher-Demo) was also created for the purpose of this research. With its help it is possible to check out how the models work. 3 | 4 | In this Playground you can create a model for: 5 | - **Image** 6 | - **Text** 7 | - **Tabular Data** 8 | 9 | classifications. 10 | 11 | It also contains a set of needed training & testing data for **classification of lunch - whether it was healthy or fast food**. *As for the images - Open Images v4 dataset and Google pictures with an option 'labeled for reuse' were used*. 12 | 13 | ## Requirements 14 | 15 | - macOS 10.14+ 16 | - Xcode 10+ 17 | --------------------------------------------------------------------------------