Android & Firebase ML Kit in Java / Kotlin
Android & Firebase ML Kit in Java / Kotlin, available at $84.99, has an average rating of 4.05, with 75 lectures, based on 138 reviews, and has 29312 subscribers.
You will learn about Learn how to make your Android Applications smart Use built in Machine Learning and computer vision models in Android Applications using Android studio Use AutoML to train model on your own dataset and develop Android Application Build Android Application to recognize different types of precious stones Develop Android Application to recognize text in images and documents Detect faces of people ,facial landmarks and facial expression Develop Android Application to scan bar codes and QR codes Develop Android Application to recognize and label images Practical application of Machine Learning Apply Machine Learning without background knowledge of ML Android Application to translate between 59 languages This course is ideal for individuals who are Beginner Android Developers want to make their applications smart or Android Developers want to use Machine Learning in their Android Applications or Developers interested in practical implementation of Machine Learning and computer vision It is particularly useful for Beginner Android Developers want to make their applications smart or Android Developers want to use Machine Learning in their Android Applications or Developers interested in practical implementation of Machine Learning and computer vision.
Enroll now: Android & Firebase ML Kit in Java / Kotlin
Summary
Title: Android & Firebase ML Kit in Java / Kotlin
Price: $84.99
Average Rating: 4.05
Number of Lectures: 75
Number of Published Lectures: 69
Number of Curriculum Items: 75
Number of Published Curriculum Objects: 69
Original Price: $89.99
Quality Status: approved
Status: Live
What You Will Learn
- Learn how to make your Android Applications smart
- Use built in Machine Learning and computer vision models in Android Applications using Android studio
- Use AutoML to train model on your own dataset and develop Android Application
- Build Android Application to recognize different types of precious stones
- Develop Android Application to recognize text in images and documents
- Detect faces of people ,facial landmarks and facial expression
- Develop Android Application to scan bar codes and QR codes
- Develop Android Application to recognize and label images
- Practical application of Machine Learning
- Apply Machine Learning without background knowledge of ML
- Android Application to translate between 59 languages
Who Should Attend
- Beginner Android Developers want to make their applications smart
- Android Developers want to use Machine Learning in their Android Applications
- Developers interested in practical implementation of Machine Learning and computer vision
Target Audiences
- Beginner Android Developers want to make their applications smart
- Android Developers want to use Machine Learning in their Android Applications
- Developers interested in practical implementation of Machine Learning and computer vision
Requirements
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You should have some basic knowledge of Android App Development using Java or Kotlin
Firebase ML Kit for Android Developer’s
Make your Android Applications smart, use ML trained model or train your own ML models explore the power of AI and Machine Learning.
This course was recorded using Android Studio 3.6.1 (which is a great introduction to the development environment!) For a smooth experience I’d recommend you use the same, but students can still use the latest Android Studio version available if they prefer!
Wish you’d thought of Object Recognition/Face Detection/Text Recognition?
Me too.
But until I work out how to build a time machine.
Here’s the next best thing.
Firebase ML Kit for Android Developer’s
Curriculum:
In this course, we will explore the features of Firebase ML Kit for Android. We will start by learning about Firebase ML Kit and Features it provides. Then we will see how to integrate ML Kit inside your Android Application just using Android studio. After that, we will explore the features of ML Kit and develop Android Applications like
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Text Recognition Android Application
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Android Application to Translate between Languages
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Language Detection Application
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Face Detection Application
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Barcode Scanner Android Application
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Object Detection Android App
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Landmark Recognition Application
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Stones Recognition Application
Then we will learn about Auto ML Vision edge feature of Firebase ML Kit using which we can train the Machine Learning model on our own dataset and build Android Application for that model. We will train model to recognize different types of stones and build an Android App for that model.
At the end of this course, we will combine different features of Firebase ML kit to build an Android Application to categorize images of mobile gallery.
Why choose me?
My name’s Hamza Asif, Udemy’s coding instructor.
It’s not my first course on mobile Machine Leaning. I have a course named “Complete Tensorflow Lite course for Android App Development” on udemy.
So which course you should take?
It’s recommended taking “Machine Learning for Android Developer using Tensorflow lite” first so that you can understand the working of Machine Learning.
If you want to learn a practical implementation and use of Machine Learning in Android using Firebase ML Kit……………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………. then that course is for you.
This is my 2nd course on Android Machine Learning and I am the only udemy instructor with more than one course on that topic. My goal is to promote the use of Machine Learning in Android and I am excited to share my knowledge with you.
Android Version we will use?
Android Pie, Android Q
All the Android Application we will develop in this course we will use Android Pie and Q to test them. So we are
So join my Firebase ML Kit for Android Developer’s course today and here’s what you’ll get
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Learn practical implementation of Text Recognition, Language Identification, Face and expression detection, Barcode scanning, Landmark Recognition, Text Translation, and Object detection and recognition inside Android App Development using Android Studio and ML kit.
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Learn how to use Auto ML to train the model on your own dataset and use those models in Android Application
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Learn about both on-device and Cloud Machine Learning
Why take this course?
Machine Learning use is at its peak so is the mobile tech but people having skills to implement both are rare. This course will enable you to empower your Android Applications with the practical implementation of Machine Learning, Computer Vision, and AI.
Having a little knowledge of Android App Development, this course will differentiate you from other developers because you will have something that is currently in demand.
This course will make provide you a smooth path to become a pro in using Machine Learning in your Applications.
This course will not just enable you to apply machine learning in limited scenarios but It will enable you to
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Prepare or download your own dataset
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Train machine learning model
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Develop Android Application
So if you have very basic knowledge of Android App Development and want to apply Machine Learning in Android Applications without knowing background knowledge of Machine Learning this course is or you.
Is this course for you?
This is a one-size-fits-all course for beginners to experts. So, this course is for you if you are:
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A total beginner, with a curious mind and a drive to make and create awesome stuff using Android App development and ML
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A fledgling developer, want to add Machine Learning implementation in his skillset
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A pro app developer-heavyweight, with an itch to build your dream app
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An entrepreneur with big ideas
Benefits to you
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Risk-free! 30-day money-back guarantee
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Freedom to work from anywhere (beach, coffee shop, airport – anywhere with Wi-Fi)
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Potential to work with forward-thinking companies (from cool start-ups to pioneering tech firms)
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Rocket-fuelled job opportunities and powered-up career prospects
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A sense of accomplishment as you build amazing things
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Make any Android app you like (your imagination is your only limit)
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Submit your apps to Google Play and potentially start selling within hours
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Use ML Kit just using Android Studio
Thanks for getting this far. I appreciate your time! I also hope you’re as excited to get started as I am to share the latest use of ML in Android development with you.
All that remains to be said, is this…
Don’t wait another moment. The world is moving fast. And I know you’ve got ideas worth sharing.
Coding really can help you achieve your dreams.
So click the button to sign up today – completely risk-free.
And join me on this trailblazing adventure, today.
Who this course is for:
-
Anyone who wants to learn the practical implementation of Machine Learning and Computer Vision in their Android Applications.
-
Anyone who wants to make their Android App Development smart.
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Anyone who wants to train and deploy Machine Learning models on his own data without background knowledge of Machine Learning.
Course Curriculum
Chapter 1: Introduction
Lecture 1: Firebase ML Kit for Android course introduction
Chapter 2: Java: Choosing or Capturing Images in Android
Lecture 1: Creating a new Android Studio Project and build GUI of Application
Lecture 2: Choosing images from Gallery in Android
Lecture 3: One more Step
Lecture 4: Capturing Images using Camera in Android
Lecture 5: Converting Images into Bitmap in Android
Lecture 6: Image Picker in Android Overview
Chapter 3: Kotlin: Choosing or Capturing Images in Android
Lecture 1: Creating a new Android Studio Project and build GUI of Application
Lecture 2: Choosing images from Gallery in Android
Lecture 3: Handling Permissions in Android
Lecture 4: Capturing Images using Camera in Android
Lecture 5: Converting Images into Bitmap in Android
Lecture 6: Image Picker in Android Overview
Chapter 4: Java: Image Labeling in Android
Lecture 1: Setting Up Image Labeling With Images Project
Lecture 2: GUI of Image Labeling With Images Android Application
Lecture 3: Documentation of Image Labeling
Lecture 4: Adding Library in Android and Preparing Images for Image Labeling
Lecture 5: Initializing Image Labeler and Performing Image Labeling
Lecture 6: Testing Image Labeling With Images Application
Lecture 7: Formatting Output and Setting Confidence threshold
Lecture 8: Image Labeling With Images Overview
Chapter 5: Kotlin: Image Labeling in Android
Lecture 1: Setting Up Image Labeling With Images Project
Lecture 2: GUI of Image Labeling With Images Android Application
Lecture 3: Documentation of Image Labeling
Lecture 4: Adding Library in Android and Preparing Images for Image Labeling
Lecture 5: Initializing Image Labeler and Performing Image Labeling
Lecture 6: Testing Image Labeling With Images Application
Lecture 7: Formatting Output and Setting Confidence threshold
Lecture 8: Image Labeling With Images Overview
Chapter 6: Recognize Text
Lecture 1: Java Creating Android and Firebase Project
Lecture 2: Java Creating Android Application GUI
Lecture 3: Java Creating and Using Text Recognizer feature of Firebase ML Kit
Lecture 4: Java Running Text Recognition Android Application
Lecture 5: Kotlin Text Recognition Android Application using Firebase ML Kit
Lecture 6: Google Services file missing error
Chapter 7: Language Identification and Assignment
Lecture 1: Message for Kotlin Developer's
Lecture 2: Android Firebase ML Kit: Creating Language Identifier
Lecture 3: Android Firebase ML Kit: Testing Language Identification Application
Lecture 4: Firebase ML Kit Assignment
Chapter 8: Translation Section
Lecture 1: Setting up Android Text Translation Android Application
Lecture 2: Writing Firebase ML kit Text Translationcode
Lecture 3: Testing Android Translation Android Application using Firebase ML Kit
Chapter 9: Scan Bar-codes
Lecture 1: Building Barcode Scanner Android Application using Firebase ML Kit
Lecture 2: Running Barcode Scanning Android Application
Chapter 10: Face and Landmark detection
Lecture 1: Setting up project Face Detection Android Project
Lecture 2: Creating and Using Face Detector feature of Firebase ML Kit Android
Lecture 3: Java Detect Faces And Drawing Rectangles Android Firebase ML Kit
Lecture 4: Java Landmark detection using Android Firebase ML Kit
Lecture 5: Java Smile Detection using Android Firebase ML Kit
Lecture 6: Kotlin Setting up Android Face detection project
Lecture 7: Kotlin Creating and Using Face Detector using Android Firebase ML Kit
Lecture 8: Kotlin Detect Faces And Drawing Rectangles using Android Firebase ML Kit
Lecture 9: Kotlin Landmark detection using Android Firebase ML Kit
Lecture 10: Kotlin Smile detection using Android Firebase ML Kit
Chapter 11: Object Detection
Lecture 1: Building Object detector Android Application using Firebase ML kit
Lecture 2: Writing object detector code using Android Firebase ML Kit
Lecture 3: Testing Android object detection Application
Chapter 12: AutoML and Stones Recognizer
Lecture 1: Creating Android and Firebase Project
Lecture 2: Android Firebase ML Kit: Arranging our dataset
Lecture 3: Android Firebase ML Kit: Training model using AutoML
Lecture 4: Android Firebase ML Kit: Downloading and evaluating model
Lecture 5: Android Firebase ML Kit: Adding Model and Creating UI
Lecture 6: Android Firebase ML Kit: Writing Recognizer Code
Chapter 13: Project
Lecture 1: Creating Project UI
Lecture 2: Initializing UI Elements
Lecture 3: Getting all phone images
Lecture 4: Writing detector code
Lecture 5: Processing all images
Lecture 6: Creating Adapter for Recyclerview
Instructors
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Mobile ML Academy by Hamza Asif
ML & AI based Flutter, Android, IOS & React Native Courses
Rating Distribution
- 1 stars: 4 votes
- 2 stars: 7 votes
- 3 stars: 26 votes
- 4 stars: 56 votes
- 5 stars: 45 votes
Frequently Asked Questions
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