HOT
blank

Flutter Mobile Ai Machine Learning Course 2024

Development

Rating3.9
Enroll Now

Flutter Mobile Ai Machine Learning Course 2024, available at $49.99, has an average rating of 3.9, with 86 lectures, based on 28 reviews, and has 277 subscribers.

You will learn about 15+ Flutter Ai Machine Learning Apps Mobile Machine Learning Mobile Deep Learning What is GetX Image Classification Neural Networks and much more This course is ideal for individuals who are anyone who wants to learn and build ai flutter apps or anyone who wants to learn and build flutter machine learning apps using getx It is particularly useful for anyone who wants to learn and build ai flutter apps or anyone who wants to learn and build flutter machine learning apps using getx.

Enroll now: Flutter Mobile Ai Machine Learning Course 2024

Summary

Title: Flutter Mobile Ai Machine Learning Course 2024

Price: $49.99

Average Rating: 3.9

Number of Lectures: 86

Number of Published Lectures: 86

Number of Curriculum Items: 86

Number of Published Curriculum Objects: 86

Original Price: $19.99

Quality Status: approved

Status: Live

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

Who Should Attend

  • anyone who wants to learn and build ai flutter apps
  • anyone who wants to learn and build flutter machine learning apps using getx

Target Audiences

  • anyone who wants to learn and build ai flutter apps
  • anyone who wants to learn and build flutter machine learning apps using getx

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.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Chapter 2: Flutter – Avengers Characters Recogniser App

Lecture 1: Create and Setup New Project – Adding Dependencies

Lecture 2: Start Training Model using Datasets

Lecture 3: Implement function for pick image from Gallery & capture image with Camera

Lecture 4: Load Trained Model

Lecture 5: Image Classification

Lecture 6: Working on Ui Design & Some Changes – Run and Testing App

Lecture 7: Source Code

Chapter 3: Flutter – Cats vs Dogs Classifier App

Lecture 1: Create & Setup a new Flutter Project And adding dependencies

Lecture 2: Implementing Pick image from Gallery & Capture Image from Camera

Lecture 3: How to Train Model using our Datasets

Lecture 4: Load Trained Model

Lecture 5: Run Model on Images and Detect whether its cat or dog

Lecture 6: Finishing and Testing Application Now

Lecture 7: Source Code

Chapter 4: Flutter – Cats Breed Identifier App

Lecture 1: Create and Setup a new Flutter Project – Installing Dependencies

Lecture 2: Implementing Capture Image from Camera & Pick image from Gallery

Lecture 3: How to load already Trained Model in Flutter Project

Lecture 4: Run Model on Images Provided by users and Identify Cats Breed

Lecture 5: Finishing & Testing Complete App Now

Lecture 6: Source Code

Chapter 5: Flutter – Face Mask Detector App

Lecture 1: Create & Setup new Flutter Project – Adding Dependencies

Lecture 2: init Live Camera Stream

Lecture 3: Adding Asset folder & Load Trained Model

Lecture 4: Implement run On Model Frame

Lecture 5: Finishing & Test Complete App

Lecture 6: Source Code

Chapter 6: Flutter – Flowers Recognition App

Lecture 1: Create & Setup a new Flutter Project – Install Dependencies

Lecture 2: Capture image with Camera & Pick Image from Gallery

Lecture 3: Adding Assets & Load Model

Lecture 4: Detect Image of Flower and Tell its name

Lecture 5: Finishing & Test Complete App

Lecture 6: Source Code

Chapter 7: Flutter – Classic Objects Recognition App

Lecture 1: Setup a new Project and adding Dependencies

Lecture 2: Implementing initCamera Function

Lecture 3: Load Trained Model and Adding Assets

Lecture 4: Implement run Model On Stream Frames

Lecture 5: Completing App & Testing App

Lecture 6: Source Code

Chapter 8: Flutter – Fruits Detection App

Lecture 1: Create & Setup new GetX Flutter Project

Lecture 2: Implementing the init Camera Function

Lecture 3: Load Fruits Trained Model & Adding Assets

Lecture 4: Implementing run Model On Stream Frames

Lecture 5: Finishing & Test App

Lecture 6: Source Code

Chapter 9: Flutter – Advanced Objects Recogniser App

Lecture 1: Setup a New Project

Lecture 2: init Camera

Lecture 3: Adding Assets & Load Model

Lecture 4: Run Model on Stream Frames

Lecture 5: Implementing Display Boxes Around Recognised Objects

Lecture 6: Code Correction

Lecture 7: Finishing & Testing App

Lecture 8: Source Code

Chapter 10: Flutter – Face Detection App using Google Machine Learning Vision

Lecture 1: Setup new Project and Adding Dependencies

Lecture 2: Connecting App to Google ML Kit Firebase

Lecture 3: Defining Variables

Lecture 4: Utils Scanner

Lecture 5: Utils Scanner for Detection and Drawing Rectangle

Lecture 6: initCamera

Lecture 7: Implement required function

Lecture 8: Face Detector Painter

Lecture 9: buildResult

Lecture 10: toggle Camera to Front or Back

Lecture 11: Finishing & Test App

Lecture 12: Source Code

Chapter 11: Flutter OCR Scanner App [Image to Text Converter App] using Google ML Vision

Lecture 1: Create and Setup a New Project

Lecture 2: Connecting App to Google ML Vision [Firebase]

Lecture 3: Pick Image from Gallery & Camera

Lecture 4: Perform Image Labelling

Lecture 5: Complete App & Test App

Lecture 6: Source Code

Chapter 12: Flutter – Dog Breeds Recognition App

Lecture 1: Create and Setup a New Flutter Project

Lecture 2: initialise Live Camera

Lecture 3: load Model & initState

Lecture 4: run Model On Live Stream Frames

Lecture 5: Finishing App & Test App

Lecture 6: Source Code

Chapter 13: Flutter – Pose Estimation App

Lecture 1: Create & Setup a New Flutter Project

Lecture 2: init Live Camera

Lecture 3: Adding Asset – load Model

Lecture 4: run Model On Stream Frame

Lecture 5: display Key Points

Lecture 6: Finishing App & Test App

Lecture 7: Source Code

Chapter 14: Congratulations – Course Finished

Lecture 1: Where to go From Here

Lecture 2: Thank you

Instructors

  • Muhammad Ali
    Muhammad Ali
    WEB & Mobile Apps Development, Game Development, AI, AR & ML

Rating Distribution

  • 1 stars: 6 votes
  • 2 stars: 2 votes
  • 3 stars: 1 votes
  • 4 stars: 2 votes
  • 5 stars: 17 votes

Frequently Asked Questions


How long do I have access to the course materials?


You can view and review the lecture materials indefinitely, like an on-demand channel.


Can I take my courses with me wherever I go?


Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

You may also like

Top 10 Ethical AI Courses to Learn in November 2024

Top 10 Game Development Courses to Learn in November 2024

Top 10 Software Testing Courses to Learn in November 2024