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Machine Learning use in Flutter, The Complete Guide

 

Machine Learning use in Flutter, The Complete Guide

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Machine Learning use in Flutter, The Complete Guide Learn use of Firebase ML Kit & TensorFlow lite for Flutter. Train ML models for Flutter, Build 15+ ML Flutter Dart Apps
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What you'll learn

  • Use of Machine Learning models in Flutter
  • Use of Firebase ML Kit in Flutter Applications
  • Use of pretrained Tensorflow lite models in Flutter
  • Training Image classification models for Flutter Applications
  • Image labeling and Barcode scanning in Flutter
  • Text Recognition and Face Detection in Flutter
  • Image classification and Object Detection in Flutter
  • Image Segmentation and Pose Estimation in Flutter
  • Using Machine learning models with images from gallery and camera in Flutter
  • Using ML models on live footage from camera in Flutter

Requirements

  • Basic Knowledge of App development in Flutter

Description

Welcome to the Machine Learning use in Flutter, The complete guide course.

Covering all the fundamental concepts of using ML models inside Flutter applications, this is the most comprehensive and only Flutter ML course available online.

We built this course over months, perfecting the curriculum, and covering everything that will help you learn to use Machine Learning models inside Flutter dart applications. This course will teach you to build powerful ML-based applications in Flutter for Android and IOS devices.

The important thing is you don't need to know background working knowledge of Machine learning and computer vision to use ML models inside Flutter and train them.

Course structure

We will start by learning about two important libraries

  • Image Picker: to chose images from the gallery or capture images using the camera
  • Camera: to get live footage from the camera frame by frame

Then we will learn about the Firebase ML kit and the features it provides. We will explore the features of the firebase ML kit and build two applications using each feature.

The applications we will build in that section are

  • Image labeling Flutter application using images of gallery and camera
  • Image labeling Flutter application using live footage from the camera
  • Barcode Scanning Flutter application using images of gallery and camera
  • Barcode Scanning Flutter application using live footage from the camera
  • Text Recognition Flutter application using images of gallery and camera
  • Text Recognition Flutter application using live footage from the camera
  • Face Detection Flutter application using images of gallery and camera
  • Face Detection Flutter application using live footage from the camera

After learning the use of Firebase ML Kit inside flutter applications we will learn the use of popular pre-trained TensorFlow lite models inside flutter applications. So we explore some popular models and build the following flutter applications in this section

  • Image classification Flutter application using images of gallery and camera
  • Image classification Flutter application using live footage from the camera
  • Object detection Flutter application using images of gallery and camera
  • Object detection Flutter application using live footage from the camera
  • Human pose estimation Flutter application using images of gallery and camera
  • Human pose estimation Flutter application using live footage from the camera
  • Image Segmentation Flutter application using images of gallery and camera
  • Image Segmentation Flutter application using live footage from the camera

After learning the use of pre-trained machine learning models using Firebase ML Kit and Tensorflow lite models inside Flutter we will learn to train our own Image classification models without knowing any background knowledge of Machine Learning. So we will learn to

  • Gether and arrange the data set for the machine learning model training
  • Training Machine learning some platforms with just a few clicks

So in that section, we will

  • Train dog breed classification model
  • Build a Flutter application to recognize different breeds of dogs
  • Train Fruit recognition model using transfer learning
  • Building a Flutter application to recognize different fruits


So the course is mainly divided  into three major sections

    In the first section, we will learn 

    • Image Labeling
    • Barcode Scanning
    • Text Recognition
    • Face Detection

    So we will explore these features one by one and build Flutter applications. For each of the features of the Firebase ML Kit, we will build two applications. In the first application, we are gonna use the images taken from the gallery or camera, and in the second application, we are gonna use the live camera footage with the Firebase ML model. So you apart from simple ML-based applications you will also be able to build real-time face detection and image labeling application in Flutter dart using the live camera footage. So after completing this section you will have a complete grip on Google Firebase ML Kit and also you will be able to use upcoming features of Firebase ML Kit for Flutter.

    After covering the Google Firebase ML Kit, In the second section of this course, you will learn about using Tensorflow lite models inside Flutter. Tensorflow Lite is a standard format for running ML models on mobile devices. So in this section, you will learn the use of pretrained powered ML models inside Flutter dart for building

    • Image Classification (ImageNet V2 model)
    • Object Detection (MobileNet model, Tiny Yolo model)
    • Pose Estimation (PostNet model)
    • Image Segmentation (Deeplab model)

    applications. So not only you will learn to use these models with images but you will also learn to use them with frames of camera footage to build real-time applications.

    So after learning the use of Machine Learning models inside Flutter dart using two different approaches in the third section of this course you will learn to train your own Machine Learning models without any background knowledge of machine learning. So in that section, we will explore some platforms that enable us to train machine learning models for mobile devices with just a few clicks. So in the third section, you will learn to

    • Collect and arrange the dataset for model training
    • Training the Machine Learning models from scratch using Teachable-Machine
    • Retraining existing models using Transfer Learning
    • Using those trained models inside Flutter dart Applications

    So we will train the models to recognize different breeds of dogs and to recognize different fruits and then build Flutter dart Applications using those models for android and IOS.

    By the end of this course, you will be able

    • Use Firebase ML kit inside Flutter dart applications for Android and IOS
    • Use pre-trained Tensorflow lite models inside Android & IOS application using Flutter dart
    • Train your own Image classification models and build Flutter applications.
    You'll also have a portfolio of over 15 apps that you can show off to any potential employer.
    Sign up today, and look forwards to:
    •  HD 1080p video content, everything you'll ever need to succeed as a Flutter Machine Learning developer.
    • Building over 15 fully-fledged apps including ones that use Objet detection, Text Recognition, Pose estimation models, and much much more.
    • All the knowledge you need to start building Machine Learning-based app you want
    • $2000+ Source codes of 15 Applications.

    REMEMBER… I'm so confident that you'll love this course that we're offering a FULL money-back guarantee for 30 days! So it's a complete no-brainer, sign up today with ZERO risks and EVERYTHING to gain.

    So what are you waiting for? Click the buy now button and join the world's best Flutter Machine Learning course.

    Who this course is for:

    • Beginner Flutter developer with very little knowledge of mobile app development in Flutter
    • Intermediate Flutter developer wanted to build a powerful Machine Learning-based application in Flutter
    • Experienced Flutter developers wanted to use Machine Learning models inside their applications.
    • Anyone who took a basic flutter mobile app development course before (like flutter app development course by angela yu or other such courses) .
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