Flutter Mobile Ai Machine Learning Course 2024

Learn and Build Flutter Android iOS Artificial Intelligence, Deep Learning, Machine Learning Applications - GetX Apps

4.10 (25 reviews)
Udemy
platform
English
language
Mobile Apps
category
instructor
262
students
8 hours
content
Mar 2024
last update
$49.99
regular price

What you will learn

15+ Flutter Ai Machine Learning Apps

Mobile Machine Learning

Mobile Deep Learning

What is GetX

Image Classification

Neural Networks

and much more

Description

In this course using flutter null safe code we will develop 15+ ai mobile applications.

GetX is an extra-light and powerful solution for Flutter. It combines high-performance state management, intelligent dependency injection, and route management quickly and practically.

Artificial intelligence is intelligence demonstrated by machines, as opposed to the natural intelligence displayed by animals including humans. Artificial intelligence is the simulation of human intelligence processes by machines, especially computer systems. Specific applications of AI include expert systems, natural language processing, speech recognition and machine vision.

Machine learning is the study of computer algorithms that can improve automatically through experience and by the use of data. It is seen as a part of artificial intelligence. Machine learning (ML) is a type of artificial intelligence (AI) that allows software applications to become more accurate at predicting outcomes without being explicitly programmed to do so. Machine learning algorithms use historical data as input to predict new output values.

Deep learning is a type of machine learning and artificial intelligence (AI) that imitates the way humans gain certain types of knowledge. While traditional machine learning algorithms are linear, deep learning algorithms are stacked in a hierarchy of increasing complexity and abstraction. Deep learning is part of a broader family of machine learning methods based on artificial neural networks with representation learning. Learning can be supervised, semi-supervised or unsupervised.

Flutter is Google's UI toolkit for building beautiful, natively compiled applications for mobile, web, desktop, and embedded devices from a single codebase. Flutter is Google's portable UI toolkit for crafting beautiful, natively compiled applications for mobile, web, and desktop from a single codebase. Flutter works with existing code, is used by developers and organizations around the world, and is free and open source.

Content

Introduction

Introduction

GetX Flutter - Avengers Characters Recogniser App

Intro - Avengers Characters Recogniser App
Create and Setup New Project - Adding Dependencies
Start Training Model using Datasets
Implement function for pick image from Gallery & capture image with Camera
Load Trained Model
Image Classification
Working on Ui Design & Some Changes - Run and Testing App
Source Code

GetX Flutter - Cats vs Dogs Classifier App

Intro - Cats vs Dogs Classifier App
Create & Setup a new Flutter Project And adding dependencies
Implementing Pick image from Gallery & Capture Image from Camera
How to Train Model using our Datasets
Load Trained Model
Run Model on Images and Detect whether its cat or dog
Finishing and Testing Application Now
Source Code

GetX Flutter - Cats Breed Identifier App

Intro - Cats Breed Identifier App
Create and Setup a new Flutter Project - Installing Dependencies
Implementing Capture Image from Camera & Pick image from Gallery
How to load already Trained Model in Flutter Project
Run Model on Images Provided by users and Identify Cats Breed
Finishing & Testing Complete App Now
Source Code

GetX Flutter - Face Mask Detector App

Intro - Face Mask Detector App
Create & Setup new Flutter Project - Adding Dependencies
init Live Camera Stream
Adding Asset folder & Load Trained Model
Implement run On Model Frame
Finishing & Test Complete App
Source Code

GetX Flutter - Flowers Recognition App

Intro - Flowers Recognition App
Create & Setup a new Flutter Project - Install Dependencies
Capture image with Camera & Pick Image from Gallery
Adding Assets & Load Model
Detect Image of Flower and Tell its name
Finishing & Test Complete App
Source Code

GetX Flutter - Classic Objects Recognition App

Intro - Objects Recognition App
Setup a new Project and adding Dependencies
Implementing initCamera Function
Load Trained Model and Adding Assets
Implement run Model On Stream Frames
Completing App & Testing App
Source Code

GetX Flutter - Fruits Detection App

Intro - Fruits Detection App
Create & Setup new GetX Flutter Project
Implementing the init Camera Function
Load Fruits Trained Model & Adding Assets
Implementing run Model On Stream Frames
Finishing & Test App
Source Code

GetX Flutter - Advanced Objects Recogniser App

Intro - Advanced Objects Recogniser App
Setup a New Project
init Camera
Adding Assets & Load Model
Run Model on Stream Frames
Implementing Display Boxes Around Recognised Objects
Code Correction
Finishing & Testing App
Source Code

Note

More new 4+ Apps - Coming Soon

Screenshots

Flutter Mobile Ai Machine Learning Course 2024 - Screenshot_01Flutter Mobile Ai Machine Learning Course 2024 - Screenshot_02Flutter Mobile Ai Machine Learning Course 2024 - Screenshot_03Flutter Mobile Ai Machine Learning Course 2024 - Screenshot_04

Reviews

Aulia
May 19, 2023
Would you like to update tftlite in your code program. It didn't worked. Contact me again if you have fix it
Steve
May 7, 2022
i have learned alot from this course. Instructor is very good in explaining the code and how each app works.
Austin
November 27, 2021
Instructor has explain things in details. Excellent course, well structured, and a great lecturer who has a good sense of humor and great skills.
Leo
November 23, 2021
1. Send some questions, only get several answers (not all questions is properly answered as expected) 2. Getx only used at the main.dart and fairly said even without getx then the project can still run. So not clear what the getx used for anyway (no proper getx like for state management project at all) 3. Some of the sample project still not using null safety 4. Some of the important "parameter" of the tflite are not explained properly (and no answer from tutor also after I asked). What still confusing is in some project, the tutor not explaining why he choose X value and in some other project at the same parameter he uses Y value. Very confusing. I think tutor should clearly explain all the parameter used in his teaching. I feel just like watching someone code with no proper detail explanation (hey, as long the code run and give some output, yes?) :) 5. the tflite library used here is deprecated (according to the message on the flutter engine output), the tutor should update the coding to use other library that is not being deprecated (thus will later no longer supported by flutter) 6. In the section 9 about advance object recognizer app, tutor did not explain how to create the tflite model that can detect "multiple object" (at the previous sections, he explain how to create model but this is to detect only 1 object). Instead, he just give the "Ready to use multiple object model" (I do no know how or where he gets this model). It is like somebody try to teach you to make a birthday cake but the birthday cake is already exist in front of you (you just need to "decorate it" without knowing how to actually "make the cake"?) Will change the rating if the tutor answer my questions, especially my last question on how to make the model in section 9 and hopefully update training material to use machine learning library that is not deprecated by flutter (As I already buy this course, it is not a free course for sure)
Евгений
November 20, 2021
GetX is only used for import, only place for using it - is GetMaterialApp, state controlled by SetState. Really, author implement GetX only for title of app. All projects are very similar, main difference in loaded assets. I can say, that there is just only 3 slightly different apps with one working screen with 150 lines of code, that can be reduced to 100 lines without losing functionality. Code mainly is awful - author doesn't understand flutter, looks like copy-paste time waste. Widgets are used extremely illiterate. It can't be recommended even for beginners, because it's like driving a car without using legs. So there is NO GetX, NO good Flutter code. All what you get - you will learn how to create assets for TensorFlow using third-party datasets and third-party utilities. It's pretty simple, and if author named his course "how to create and use AI models in practice with Flutter" - this course can reach at least 3 stars of 5.
Muhammad
October 26, 2021
Amazing and Excellent course. Brilliant teaching by a highly qualified instructor who knows what he is talking about and, most importantly, how to bring it across. Course is engaging, Both his teaching method and strategy are outstanding. Content is highly relevant and of priceless value: above all expectations. thanks

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4363168
udemy ID
10/23/2021
course created date
11/13/2021
course indexed date
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