Machine Learning for Flutter – The Complete 2023 Guide | Udemy


Machine Learning for Flutter – The Complete 2023 Guide | Udemy
English | Size: 8.03 GB
Genre: eLearning

TensorFlow lite & ML Kit use in Flutter, Train ML Models for Flutter ,Build 20+ Flutter Android and IOS Applications

What you’ll learn
Learn Use of Machine Learning & Computer Vision in Flutter
Train Machine Learning Models on your Custom Datasets
Use Pre-Trained Tensorflow Lite Models in Flutter
Train Custom Models for Object Detection
Train Custom Models for Image Classification
Use Computer vision models with both images & Live Camera Footage
Text Recognition In Flutter
Face & Facial Landmarks, contours & expression detection in Flutter
Text Translation in Flutter
Human Pose Estimation in Flutter
Image Labeling / Image Classification in Flutter
Object Detection in Flutter
Recognize handwritten text / Digital Ink Recognition in Flutter
Smart Reply in Flutter
Entity Extraction in Flutter
Barcode Scanning in Flutter

Welcome to the Machine Learning use in Flutter The Complete 2023 Guide.

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 ( 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. So a complete computer vision package for Flutter.

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

Train Machine Learning models on Custom datasets for Image Classification & Object Detection

Choosing images from the gallery ad capturing images using the 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)

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

Smart Reply in Flutter

Digital Ink Recognition in Flutter

Language Identification in Flutter

Training image classification models for Flutter (Android and IOS) applications

Training object detection 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

Course structure

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

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

Object Detection Flutter application using images of gallery and camera

Object Detection Flutter application using live footage from the camera

Smart Reply Flutter Application to generate smart reply suggestions in chat applications

Digital Ink Recognition Application to Recognize handwritten text

Entity Extraction Flutter Application to extract different entities from text

Pose Detection Flutter application using images of gallery and camera

Pose Detection Flutter application using live footage from the camera

Text Translation Flutter Application to translate between any two language

Language Identification Flutter Application to identify the language of text

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 MobileNet & EfficientNet models

Realtime Image classification Flutter application using MobileNet & EfficientNet models

Object detection Flutter application using MobileNet & EfficientNet models

Realtime Object detection Flutter application using MobileNet & EfficientNet models

So you will be able to train computer vision models for both Android & IOS using Flutter.

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 & object detection models without knowing any background knowledge of Machine Learning. So we will learn to

Gather and arrange the dataset for the machine learning model training

Train Machine Learning Models for Image Classification & Object Detection

Test those models

Convert models into TensorFlow lite format

Use them in Flutter with Images & Live Camera Footage

So in that section, we will

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

Object Detection in Flutter with Images and live camera footage

Pose Detection in Flutter with Images and live camera footage

Smart Reply in Flutter

Text Translation in Flutter

Language Identification In Flutter

Digital Ink Recognition in Flutter

Entity Extraction in Flutter

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 model & EfficientNet model )

Object Detection Flutter ( MobileNet model & EfficientNet 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 a complete Flutter computer vision package for Flutter.

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

Retraining existing models using Transfer Learning

Using those trained models inside Google Flutter dart Applications

So we will train the models to recognize different fruits and then build Google Flutter Applications using those Computer Vision 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 applications using Google Flutter dart

Train your own Image classification & Object Detection models and build Flutter applications.

You’ll also have a portfolio of over 20 Machine Learning & Computer Vision based 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 20 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

$2500+ Source codes of 20 Applications.

REMEMBER… I’m so confident that you’ll love this course and you will also get 30-day money-back guarantee from udemy. So it’s a complete no-brainer, sign up today.

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

An 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 & computer vision models inside their applications.

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

Developers Who want to train custom Machine Learning & computer vision models for Image Classification & Object Detection

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

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