The Complete 2021 Android Machine Learning course

欢迎来到完整的 2021 年 Android 机器学习课程。

在本课程中，您将在不了解任何机器学习背景知识的情况下学习机器学习在 Android 中的使用。

在现代世界应用程序开发中，必须在移动应用程序开发中使用 ML。我们几乎看不到未使用 ML 的应用程序。因此，了解如何将 ML 模型集成到 Android 应用程序中非常重要。本课程将教您这一点。其主要特点是您无需了解 ML 的任何背景知识即可将其集成到您的应用程序中。

课程分为三个主要部分。

预训练 Tensorflow Lite
Firebase ML Kit
训练图像分类模型

在第一部分中，您将学习在 Android 中使用流行的预训练机器学习模型并构建

图像分类
目标检测
图像分割
应用

量化和委托

除此之外，我们将涵盖与 Tensorflow lite 相关的所有重要概念，例如

在Android中使用浮点和量化模型
使用Tensorflow lite Delegates提高模型性能
Regression In Android

之后，我们将学习在 Android 中使用回归模型并构建几个应用程序，包括

车辆燃油效率预测器。
Firebase 机器学习套件

然后下一部分与 Firebase ML Kit 相关。在本节中，我们将探索

Firebase ML Kit 的 Firebase ML Kit
特性
然后我们将探索这些特性并构建许多应用程序，包括

图像标记
条码扫描
姿势估计
自拍分割
数字墨水识别
对象检测
文本识别
智能回复
文本翻译人
脸检测
CamScanner克隆

除了所有这些应用程序，我们还在开发著名的文档扫描应用程序 CamScanner 的克隆版。

训练图像分类模型

在第三节掌握了 ML 模型在 Android 中的使用后，我们将在不了解任何机器学习背景知识的情况下学习训练我们自己的图像分类模型。

因此，在该部分中，我们将学习使用两种不同的方法训练 ML 模型。

使用 Teachable Machine 进行犬种识别

首先，我们将使用可教机器训练狗品种识别模型。
构建一个实时喂食犬品种识别 Android 应用程序。
使用迁移学习的水果识别

使用迁移学习，我们将重新训练 MobileNet 模型以识别不同的水果。
使用经过训练的模型
图像和实时相机镜头构建实时饲料水果识别 Android 应用程序

本课程将教您使用带有图像和实时摄像机镜头的机器学习模型，以便您可以构建简单和实时的 Android 应用程序。

安卓版

该课程是完全最新的，我们在整个课程中都使用了最新的 Android 11。

语言

该课程是使用 Java 和 Kotlin 编程语言开发的。因此，所有材料都以两种语言提供。

在本课程结束时，您将能够

在使用 Java 和 Kotlin 的 Android 应用程序中使用 Firebase ML 套件在使用 Java 和 Kotlin 的
Android 和 IOS 应用程序中使用预先训练的 Tensorflow Lite 模型
训练您自己的图像分类模型并构建 Android 应用程序。
您还将拥有 20 多个应用程序组合，您可以向任何潜在雇主炫耀。

Duration: 1h 35m | 22 Lessons | Video: 1280×720, 44kHz | 732 MB
Genre: eLearning | Language: English | Level: All

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 are developing a clone of the famous document scanning application CamScanner.

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.

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+ apps that you can show off 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.