Tensorflow Lite For Flutter - Build Smart Flutter Apps

Learn use of Machine Learning models in Flutter and Train ML models for Google Flutter | Build 10+ Flutter Applications

What you'll learn

Use of Tensorflow lite models in Flutter

Training Image classification model and Building Flutter Applications

Using Regression model in Flutter

Building live feed Object Detection , Image Segmentation Flutter applications

Building live feed image classification , Pose estimation Flutter applications

Training Fruit Recognition model and building Flutter Application

Building Dog breed recognition Flutter Application

Building a Fuel Efficiency predictor Flutter application (Regression)

Learn to choose or capture images in Flutter

Learn to display live camera footage in Flutter

Requirements

Basic Knowledge of App development in Flutter

Developer who knows to develop Hello World Application in Flutter

Description

Do you want to build Machine Learning based Android and IOS applications?Then welcome to "Tensorflow lite for Flutter 2021, Smart App Development course"This course will teach you to build powerful ML-based Flutter applications using Tensorflow lite models. Covering all the fundamental concepts of using ML models inside Google  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 training them for Flutter applications. Starting from a very simple example course will teach you to use advanced machine learning 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 training your own models for your Flutter dart ( Android & IOS ) applications.What we will cover in this course?Dealing with Images in FlutterDealing with frames of live camera footage in FlutterImage classification with images and live camera footage in FlutterObject Detection with Images and Live Camera footage in FlutterImage Segmentation to make images transparent in FlutterPose Estimation Flutter to detect human body jointsUse of regression models in FlutterBuilding a fuel efficiency predictor Application in FlutterTraining image classification models for FlutterRetraining existing machine learning models with transfer learning  for Flutter applicationsUsing our custom models in Flutter with ImagesUsing our custom models in Flutter with live camera footageImages and Live Camera Footage in FlutterWe will start by learning about two important librariesImage Picker: to choose images from the gallery or capture images using the camera in Google Flutter (Android and IOS)Camera: to get live footage from the camera frame by frame in Google Flutter (Android and IOS)Pretrained Tensorflow lite modelsAfter that, we will learn the basics of TensorFlow lite models. Then we will learn the use of popular pre-trained models in Flutter for BuildingImage Classification(Using images or live camera footage) in Google Flutter (Android and IOS)Object Detection(Using images or live camera footage) in Google  Flutter (Android and IOS)Pose Estimation(Using images or live camera footage) in Google  Flutter (Android and IOS)Image Segmentation in Flutter (Android and IOS)applications. Tensorflow Lite is a standard format for running ML models on mobile devices. So in this section, we will use the following popular models for building these applicationsImageNet V2 model  for Image Classification Flutter application MobileNet model, Tiny YOLO model for Object Detection Flutter application PostNet model for Pose Estimation Flutter application Deeplab model for Image Segmentation Flutter application Regression modelsAfter that, we will learn to analyze and use regression models in Google Flutter and build a couple of applications including Basic Regression Example for Google Flutter (Android and IOS)Fuel Efficiency predictor for vehicles for Google Flutter (Android and IOS)Training Image Classification modelsAfter that, we will explore some platforms to train image classification models without knowing any background knowledge of Machine learning.So we will learn to get the dataset from Kaggle. After that, we will train the model to recognize different breeds of dogs and build a Flutter (Dart) application for that model.Then using a technique called transfer learning we will retrain the mobile net model on our Fruit dataset and build a Google Flutter (Dart) application for that model.After taking this course You will be able to use pre-trained ML(Machine Learning) models in your Google Flutter Applications.You can train your own Image classification models for FlutterYou will have 10+ powerful ML(Machine Learning)-based Google  Flutter dart Applications to empower your ResumeSo this course will boost your mobile app development career give your company a huge competitive advantageThe underlying motivation for this course is that you can use ML(Machine Learning) models in your own Flutter dart(Android & IOS) applicationsImpress potential employers with your Google Flutter dart ML abilitiesSign up today and you will:Understand Machine Learning models use in Flutter dartUse of ML models both with Images and Live camera footage in Google FlutterLearn how to optimize applications using Machine learning and computer visionDelight your users with complex animationsExpose the functionality of your flutter apps with computer vision modelsSteer through the incredible amount of Flutter documentationMaster use of simple and advance regression models in Flutter dartTrain machine learning models for Flutter dart applicationsImplement those models in Flutter dartHandle frames of live camera footage in Flutter dartHD 1080p video content, everything you'll ever need to succeed as a Google Flutter Machine Learning developer.Building fully-fledged Machine Learning based Flutter Applications.All the knowledge you need to start building Machine Learning-based app you want$1500+ Source codes of 10 Flutter dart 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.Who this course is for:Beginner Flutter developer with little knowledge of mobile app development in Google FlutterIntermediate Flutter developer wanted to build a powerful Machine Learning-based application in Google FlutterExperienced Google Flutter developers wanted to use Machine Learning models inside their applications.Anyone who took a basic Google flutter mobile app development course before (like flutter app development course by angela yu or other such courses).

Overview

Section 1: Introduction

Lecture 1 Introduction

Lecture 2 Tensorflow lite Introduction

Section 2: Camera and Image Picker Package

Lecture 3 Creating Image Picker Flutter Application GUI

Lecture 4 Flutter Image Picker and Choosing Images from Gallery

Lecture 5 Image Picker and Capturing Images using Camera

Lecture 6 Setting up the Camera Package in Flutter

Lecture 7 Flutter writing camera package code

Section 3: Pretrained Model Section

Lecture 8 Section Introduction

Section 4: Image Classification in Flutter using MobileNet Model

Lecture 9 Flutter Image classification Section introduction

Lecture 10 Importing Starter code for Flutter Image classification application

Lecture 11 Starter code explanation for Flutter Image classification

Lecture 12 Writing flutter image classification code

Lecture 13 Testing flutter image classification application

Lecture 14 Importing Flutter live feed Image classification application starter code

Lecture 15 Starter code explanation of Flutter Live feed Image classification application

Lecture 16 Writing Flutter Image classification code

Lecture 17 Testing live feed image classification flutter application

Section 5: Object Detection in Flutter using Yolo and SSD MobileNet model

Lecture 18 Flutter Object detection section introduction

Lecture 19 Importing Application code object detection flutter

Lecture 20 Flutter Object detection code

Lecture 21 Flutter Drawing Rectangles around detected objects

Lecture 22 Importing the code for live feed object detection flutter application

Lecture 23 Testing object detection live feed flutter application

Lecture 24 Flutter Live feed object detection application code

Section 6: Pose Estimation in Flutter using PoseNet model

Lecture 25 Flutter Pose estimation section introduction

Lecture 26 Importing Flutter Pose estimation Application code

Lecture 27 Flutter Pose estimation code

Lecture 28 Importing pose estimation live feed flutter application code

Lecture 29 Flutter Live feed pose estimation application demo

Lecture 30 Using PoseNet model for Flutter Live feed pose estimation application

Section 7: Image Segmentation in Flutter using Deeplab model

Lecture 31 Flutter Image Segmentation Section Introduction

Lecture 32 Importing Flutter Image Segmentation Application code

Lecture 33 Flutter using DeepLab model for image segmentation

Section 8: Regression in Flutter

Lecture 34 Regression in Flutter Section Introduction

Lecture 35 Importing the starter code for Basic Regression Application

Lecture 36 Flutter Basic Example starter code explaination

Lecture 37 Analyzing a regression model

Lecture 38 Adding the model in Flutter Application and testing

Lecture 39 Basic Example regression model code

Section 9: Fuel Efficiency Predictor Regression Application

Lecture 40 Analyzing Fuel Efficiency model

Lecture 41 Code for Fuel Efficiency regression model

Lecture 42 Fuel Efficiency Prediction Flutter Application

Section 10: Training Image Classification models

Lecture 43 Section Introduction

Lecture 44 Machine Learning and Image classification

Section 11: Dog Breed Recognition model and Application in Flutter

Lecture 45 Flutter Getting the dataset for model training

Lecture 46 Flutter Training the model

Lecture 47 Flutter Dog Breed Classification Application

Lecture 48 Flutter Live feed dog breed classification application

Lecture 49 Testing live feed dog breed classification application

Section 12: Fruit Recognition in Flutter using Transfer Learning

Lecture 50 Transfer Learning introduction

Lecture 51 Flutter Getting the dataset for model training

Lecture 52 Flutter Training fruit recognition model

Lecture 53 Flutter Testing Live feed fruits recognition application

Beginner Flutter developer want to learn use of Machine learning in Flutter,Intermediate Flutter developer looking to enhance their skillset,Expert Flutter developer want to build state of the art Applications,Flutter Developers want to learn Tensorflow lite models in Flutter