Genre: eLearning | MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 8.01 GB | Duration: 20h 33m
TensorFlow lite & Firebase ML Kit use in Android 11 , Train Machine Learning Models, 20+ ML based Android Applications

What you'll learn
How to Integrate Machine Learning Models in Android
Use computer vision models with Images and Live Camera Footage
Use of Tensorflow lite models in Android
Use of Floating point and quantized models in Android
Use of Tensorflow lite delegates to improve model performance
Training Image Recognition models without knowing any background knowledge of machine learning
Firebase ML Kit and the Features it Provides
20+ Machine Learning based Android Application

Description
Welcome to The Complete 2021 Android Machine Learning Course.

In this course, you will learn the use of Machine learning in Android without knowing any background knowledge of machine learning.

In modern world app development, the use of ML in mobile app development is compulsory. We hardly see an application in which ML is not being used. So it's important to learn how we can integrate ML models inside Android applications. And this course will teach you that. And the main feature of this is you don't need to know any background knowledge of ML to integrate it inside your application.

The course is divided into three main parts.

Pre-Trained Tensorflow Lite

Firebase ML Kit

Training Image Classification models

Pre-Trained Tensorflow Lite

In the first section, you will learn the use of popular pre-trained machine learning models in Android and build

Image classification

Object detection

Image segmentation

applications

Quantization and Delegates

Apart from that, we will cover all the important concepts related to Tensorflow lite like

Using floating-point and quantized model in Android

Use the use of Tensorflow lite Delegates to improve model performance

Regression In Android

After that, we will learn to use regression models in Android and build a couple of applications including a

Fuel Efficiency Predictor for Vehicles.

Firebase ML Kit

Then the next section is related to the Firebase ML Kit. In this section, we will explore

Firebase ML Kit

Features of Firebase ML Kit

Then we are going to explore those features and build a number of applications including

Image Labeling

Barcode Scanning

Pose Estimation

Selfie Segmentation

Digital Ink Recognition

Object Detection

Text Recognition

Smart Reply

Text Translation

Face Detection

CamScanner Clone

Apart from all these applications, we will be developing a clone of the famous document scanning application CamScanner. So in that application, we will auto crop the document images using text recognition and improve the visibility of document Images.

Training Image Classification Models

After mastering the use of ML Models in Android in the Third section we will learn to train our own Image Classification models without knowing any background knowledge of Machine learning.

So in that section, we will learn to train ML models using two different approaches.

Dog breed Recognition using Teachable Machine

Firstly we will train a dog breed recognition model using a teachable machine.

Build a Live Feed Dog Breed Recognition Android Application.

Fruit Recognition using Transfer Learning

Using transfer learning we will retrain the MobileNet model to recognize different fruits.

Build a live feed fruit recognition Android application using that trained model

Images and Live Camera Footage

The course will teach you to use Machine learning models with images and live camera footage, So that, you can build both simple and live feed Android applications.

Android Version

The course is completely up to date and we have used the latest Android 11 throughout the course.

Language

The course is developed using both Java and Kotlin programming languages. So all the material is available in both languages.

Tools:

These are tools we will be using throughout the course

Android Studio to develop Android Applications

Google collab to train Image Recognition models.

Netron to analyze mobile machine learning models

By the end of this course, you will be able

Use Firebase ML kit inside Android applications using both Java and Kotlin

Use pre-trained Tensorflow lite models inside Android & IOS applications using Java and Kotlin

Train your own Image classification models and build Android applications.

You'll also have a portfolio of over 20+ machine learning-based Android applications that you can show to any potential employer.

Who can take this course:

Beginner Android ( Java or Kotlin ) developer with very little knowledge of Android app development.

Intermediate Android ( Java or Kotlin ) developer wanted to build a powerful Machine Learning-based application in Android

Experienced Android ( Java or Kotlin ) developers wanted to use Machine Learning models inside their Android applications.

Anyone who took a basic Android ( Java or Kotlin ) mobile app development course before (like Android ( Java or Kotlin ) app development course by angela yu or other such courses).

Unlike any other Android app development course, The course will teach you what matters the most.

So what are you waiting for? Click on the Join button and start learning.

Who this course is for:
Beginner Android Developer curious about Machine learning and computer vision use in Android
Intermediate Android developers looking to enhance their skillset
Experienced Professional want to integrate Machine Learning in their Android Applications

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