Learn the smart way of using machine learning in Flutter to build smart android and iOS applications with the Machine Learning in Flutter: Complete Guide course.
Flutter is a software development kit for developing beautiful applications from a single codebase. Moreover, if you can infuse machine learning within Flutter, you can craft wonders. This complete guide aims to provide you with the fundamental knowledge and skills required to use Machine Learning in Flutter to equip you with this phenomenal skill.
This complete guide will give you a solid foundation of the Firebase ML kit as well as a detailed idea about the image picker library and camera package setup for Flutter. You will explore a broad range of flutter widgets like image labelling, face detection, pose estimation and so on.
Enrol in this Machine Learning in Flutter: Complete Guide course today and build high-quality and functionally-rich apps using machine Learning in Flutter.
Familiar yourself with the recent development and updates of the relevant industry
Know how to use your theoretical knowledge to adapt in any working environment
Get help from our expert tutors anytime you need
Access to course contents that are designed and prepared by industry professionals
Study at your convenient time and from wherever you want
Module 03: Flutter using DeepLab model for image segmentation
Unit 13: Section Training Image Classification Models
Module 01: Section Introduction
Module 02: Machine Learning and Image classification
Unit 14: Dog Breed Classification
Module 01: Flutter getting the dataset for model training
Module 02: Flutter Training the model
Module 03: Flutter Dog Breed Classification Application
Module 04: Flutter Live feed dog breed classification application
Module 05: Testing live feed dog breed classification application
Unit 15: Fruits Recognition using Transfer Learning
Module 01: Transfer learning introduction
Module 02: Flutter getting the dataset for model training
Module 03: Flutter Training fruit recognition model
Module 04: Flutter Testing Live feed fruits recognition application
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