BUY MACHINE LEARNING FOR FLUTTER THE COMPLETE GUIDE - FLUTTER ML

MACHINE LEARNING FOR FLUTTER THE COMPLETE GUIDE - FLUTTER ML





Welcome to the Machine Learning for Flutter The Complete Guide - Flutter ML course. Covering all the fundamental concepts of using ML models inside Flutter applications, this is the most comprehensive Google Flutter ML course available online. 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 2.0 ( Dart ) and train them.


Important Notice: Firebase ML Kit section of course is updated with the new package.

Starting from a very simple example course will teach you to use advanced ML models in your Flutter ( Android & IOS ) Applications. So after completing this course you will be able to use both simple and advance Tensorflow lite models along with a Firebase ML Kit in your Flutter ( Android & IOS ) applications.

Course structure

We will start by learning about two important libraries

1. Image Picker: to chose images from the gallery or capture images using the camera in Flutter
   
   
2. Camera: to get live footage from the camera frame by frame in Flutter
   

So later we can use a computer vision model with both images and live camera footage in Flutter.

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 flutter applications using each feature.

The flutter 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
  
  
• 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 Google Flutter (Android& IOS) applications we will learn the use of popular pre-trained TensorFlow lite models inside Google Flutter applications. So we explore some popular models and build the following Google 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 that, we will learn to use Regression models in Google Flutter and build a couple of applications including

• Basic Regression Flutter Application for Android and IOS
  
  
• Fuel Efficiency predictor for vehicles in Flutter for Android and IOS
  

After learning the use of pre-trained machine learning models using Firebase ML Kit and Tensorflow lite models inside Flutter ( Dart ) 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 a dog breed classification model for Flutter
  
  
• Build a Flutter ( Android & IOS ) application to recognize different breeds of dogs
  
  
• Train Fruit recognition model using Transfer learning
  
  
• Building a Flutter ( Android & IOS ) application to recognize different fruits
  

So the course is mainly divided into three major sections

• Firebase ML Kit for Flutter
  
  
• Pretrained TensorFlow lite models for Flutter
  
  
• Training image classification models for Flutter
  

In the first section, we will learn the use of Firebase ML Kit inside the Flutter dart applications for common use cases like

• Image Labeling in Flutter with Images and live camera footage
  
  
• Barcode Scanning in Flutter with Images and live camera footage
  
  
• Text Recognition in Flutter with Images and live camera footage
  
  
• Face Detection in Flutter with Images and live camera footage
  

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 Google 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 Google Flutter ( Dart ).

After covering the Google Firebase ML Kit, In the second section of this course, you will learn about using Tensorflow lite models inside Google Flutter ( Dart ). 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 Google Flutter dart for building

• Image Classification Flutter ( ImageNet V2 model )
  
  
• Object Detection Flutter ( MobileNet model, Tiny YOLO model)
  
  
• Pose Estimation Flutter ( PostNet model )
  
  
• Image Segmentation Flutter ( 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 flutter 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 Google Flutter dart Applications
  

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

By the end of this course, you will be able

• Use Firebase ML kit inside Google Flutter dart applications for Android and IOS
  
  
• Use pre-trained Tensorflow lite models inside Android & IOS application using Google Flutter dart
  
  
• Train your own Image classification models and build Flutter applications.
  

You'll also have a portfolio of over 15 Flutter apps that you can show off to any potential employer.