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CONTENT:
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
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
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
After that, we will learn to use regression models in Android and build a couple of applications including a
- Fuel Efficiency Predictor for Vehicles.
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
- Image Labeling
- Barcode Scanning
- Pose Estimation
- Selfie Segmentation
- Digital Ink Recognition
- Object Detection
- Text Recognition
- Smart Reply
- Text Translation
- Face Detection
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.
- 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
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.
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).
So what are you waiting for? Click on the Join button and start learning.
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