Machine Learning for Flutter The Complete Guide - Flutter ML
What you'll learn
- Use of Machine learning models with images from gallery and camera in Flutter
- Use of Machine Learning models with live camera footage in Flutter
- Use of Tensorflow lite models in Flutter
- Training Machine Learning models for Flutter Applications
- How to integrate Firebase ML Kit in Flutter Applications
- Live Feed Image classification and Object Detection in Flutter
- Image Segmentation and Pose Estimation in Flutter
- Using Regression models in Flutter applications
- Image labeling and Barcode scanning in Flutter
- Text Recognition and Face Detection in Flutter
- Text Translation and Language identification in Flutter
- Building Machine learning based Realtime Flutter Applications
- Machine Learning models use in Flutter to build Smart Android and IOS Applications
- Basic Knowledge of Mobile App development in Flutter
- Developer who knows to develop Hello World Application in Flutter
Important Notice: Firebase ML Kit section of course is updated with the new package.
Welcome to the Machine Learning use in 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 your custom machine learning models.
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 advanced Tensorflow lite models along with a Firebase ML Kit in your Flutter ( Android & IOS ) applications.
What we will cover in this course?
Learning the use of existing machine learning models in Flutter (Android and IOS) applications
Learn to train your own custom machine learning models and build Flutter applications
Choosing images from gallery ad capturing images using camera in Flutter
Displaying live camera footage and fetching frames of live camera footage in Flutter
Image classification with images and live camera footage in Flutter (Android and IOS)
Object Detection with Images and Live Camera footage in Flutter (Android and IOS)
Image Segmentation to make images transparent in Flutter (Android and IOS)
Use of regression models in Flutter (Android and IOS)
Image Labeling Flutter to recognize different things
Barcode Scanning in Flutter to scan barcodes and QR codes
Pose Estimation in Flutter to detect human body joints
Text Recognition in Flutter to recognize text in images
Text Translation in Flutter to translate between different languages
Face Detection in Flutter to detect faces, facial landmarks, and facial expressions
Training image classification models for Flutter (Android and IOS) applications
Retraining existing machine learning models with transfer learning for Flutter (Android and IOS) applications
Using our custom machine learning models in Flutter (Android and IOS) applications
We will start by learning about two important libraries
Image Picker: to choose images from the gallery or capture images using the camera in Flutter
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 machine learning 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.
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 flutter applications 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 Flutter (Android or IOS) application 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).
Who this course is for:
- Anyone who took Basic Flutter course before
- Beginner Flutter Developer curious about Machine learning and computer vision use in Flutter
- Experienced Professional want to add ML models in their Flutter Applications
- App developer want to learn use of Machine learning in their Flutter Applications
- Intermediate Flutter developers looking to enhance their skillset
Experienced Mobile Developer, specialized in Mobile Machine Learning using Tensorflow lite, ML Kit, and Google cloud vision API. Leading Android Machine learning instructor with over 50,000 students from 150 countries.
I am an enthusiastic developer with a strong programming background and possess great app development skills. I have developed a bunch of native and cross-platform apps in the past and satisfied all of my clients. It has been +4 years doing Mobile development and providing support for Android Applications. Empowering mobile Applications using Machine Learning and Computer vision is my core skill.
Powering Android Application with ML really fascinates me. So I learned Android development and then Machine Learning. I developed Android applications for several multinational organizations. Now I want to spread the knowledge I have. I'm always thinking about how to make difficult concepts easy to understand, what kind of projects would make a fun tutorial, and how I can help you succeed through my courses.