Machine Learning use in Flutter The Complete Guide

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 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.

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

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

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 dog breed classification model

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

Pretrained TensorFlow lite models

Training image classification models

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

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 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 ( 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 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 dart 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.

Sign up today, and look forwards to:

HD 1080p video content, everything you’ll ever need to succeed as a Google 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 Google Flutter ( Dart ) Machine Learning course.

Who this course is for:

Beginner Flutter ( Dart ) developer with very little knowledge of mobile app development in Google Flutter

Intermediate Flutter ( Dart ) developer wanted to build a powerful Machine Learning-based application in Google Flutter

Experienced Flutter ( Dart ) developers wanted to use Machine Learning models inside their applications.

Anyone who took a basic flutter ( Dart ) mobile app development course before (like Flutter ( Dart ) app development course by angela yu or other such courses).