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README.md

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+## Machine Learning use in React Native The Practical Guide
+
+> 👷 Developed by Matheus Ramalho de Oliveira  
+🔨 Brazilian Software Engineer  
+🏡 Goiânia, Goiás, Brasil  
+✉️ kastorcode@gmail.com  
+👍 [instagram.com/kastorcode](https://www.instagram.com/kastorcode)
+
+---
+
+<p align="center">
+  <img src="android/app/src/main/res/mipmap-xxxhdpi/ic_launcher_round.png" width="96" />
+</p>
+
+<p align="center">
+  How to use machine learning in React Native applications? This app is about answering this question through models from the TensorFlow Lite library.
+</p>
+
+<p align="center">
+  Architected and programmed during the Machine Learning use in React Native The Practical Guide course.
+</p>
+
+---
+
+### Screenshots
+
+<p align="center">
+  <img src="screenshots/0.png" width="720" />
+</p>
+
+<p align="center">
+  <img src="screenshots/1.png" width="720" />
+</p>
+
+<p align="center">
+  <img src="screenshots/2.png" width="720" />
+</p>
+
+<p align="center">
+  <img src="screenshots/3.png" width="720" />
+</p>
+
+<p align="center">
+  <img src="screenshots/4.png" width="720" />
+</p>
+
+<p align="center">
+  <img src="screenshots/5.png" width="720" />
+</p>
+
+<p align="center">
+  <img src="screenshots/6.png" width="720" />
+</p>
+
+---
+
+### Tools used
+
+[Git](https://git-scm.com)  
+[Google Colab](https://colab.research.google.com)  
+[Kaggle](https://kaggle.com)  
+[React Native](https://reactnative.dev)  
+[Teachable Machine](https://teachablemachine.withgoogle.com)  
+[TensorFlow Lite](https://tensorflow.org/lite)  
+[TypeScript](https://typescriptlang.org)  
+[Visual Studio Code](https://code.visualstudio.com)
+
+---
+
+### Topics covered
+
+1. Creating a new React Native project;
+2. Creating GUI of the application;
+3. Choosing images from gallery;
+4. Capturing images using camera;
+5. Adding TensorFlow Lite models inside React Native project;
+6. Performing image classification;
+7. Performing image classification with live camera footage;
+8. Performing object detection;
+9. Performing pose estimation;
+10. Performing image segmentation;
+11. Showing predictions on screen;
+12. Training image classification model;
+13. Dog breed recognition with images;
+14. Training fruit recognition model with transfer learning;
+15. Retraining other models;
+16. Fruit recognition using live camera footage.
+
+---
+
+### 🧠 Installation and execution
+
+1. Make a clone of this repository;
+2. Open the project folder in a terminal;
+3. Run `yarn` to install dependencies;
+4. Run the commands `yarn start` and `yarn android` to start Metro server and compile the app;
+5. Start coding!
+
+---
+
+<p align="center">
+  <img src="src/assets/images/kastorCodeLogo.png" width="96" />
+</p>