Genre: eLearning | MP4 | Video: h264, 1280×720 | Audio: aac, 44100 Hz
Language: English | VTT | Size: 3.34 GB | Duration: 5h 8m
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
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 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) .
Who this course is for:
Beginner Flutter Developer curious about ML use in Flutter
Experienced Professional want to add ML models in theirApplications
App developer want to learn use of ML in their Applications
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