[ FreeCourseWeb ] Udemy - Android & Firebase ML Kit in Java - Kotlin

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[ FreeCourseWeb.com ] Udemy - Android & Firebase ML Kit in Java - Kotlin
  • Get Bonus Downloads Here.url (0.2 KB)
    • ~Get Your Files Here ! 1. Introduction
    • 1. Firebase ML Kit for Android course introduction.mp4 (21.5 MB)
    • 2. Firebase ML Kit Features.mp4 (11.9 MB)
    2. Recognize Text
    • 1. Java Creating Android and Firebase Project.mp4 (33.0 MB)
    • 2. Java Creating Android Application GUI.mp4 (69.5 MB)
    • 3. Java Creating and Using Text Recognizer feature of Firebase ML Kit.mp4 (129.0 MB)
    • 4. Java Running Text Recognition Android Application.mp4 (105.9 MB)
    • 5. Kotlin Text Recognition Android Application using Firebase ML Kit.mp4 (218.8 MB)
    • 6. Google Services file missing error.mp4 (25.7 MB)
    3. Language Identification and Assignment
    • 1. Message for Kotlin Developer's.mp4 (13.6 MB)
    • 2. Android Firebase ML Kit Creating Language Identifier.mp4 (61.4 MB)
    • 3. Android Firebase ML Kit Testing Language Identification Application.mp4 (12.8 MB)
    • 4. Firebase ML Kit Assignment.mp4 (11.5 MB)
    4. Translation Section
    • 1. Setting up Android Text Translation Android Application.mp4 (116.3 MB)
    • 2. Writing Firebase ML kit Text Translationcode.mp4 (63.0 MB)
    • 3. Testing Android Translation Android Application using Firebase ML Kit.mp4 (43.0 MB)
    5. Scan Bar-codes
    • 1. Building Barcode Scanner Android Application using Firebase ML Kit.mp4 (135.0 MB)
    • 2. Running Barcode Scanning Android Application.mp4 (30.3 MB)
    6. Face and Landmark detection
    • 1. Setting up project Face Detection Android Project.mp4 (46.0 MB)
    • 10. Kotlin Smile detection using Android Firebase ML Kit.mp4 (44.4 MB)
    • 2. Creating and Using Face Detector feature of Firebase ML Kit Android.mp4 (59.1 MB)
    • 3. Java Detect Faces And Drawing Rectangles Android Firebase ML Kit.mp4 (34.3 MB)
    • 4. Java Landmark detection using Android Firebase ML Kit.mp4 (33.0 MB)
    • 5. Java Smile Detection using Android Firebase ML Kit.mp4 (33.9 MB)
    • 6. Kotlin Setting up Android Face detection project.mp4 (31.6 MB)
    • 7. Kotlin Creating and Using Face Detector using Android Firebase ML Kit.mp4 (117.3 MB)
    • 8. Kotlin Detect Faces And Drawing Rectangles using Android Firebase ML Kit.mp4 (38.2 MB)
    • 9. Kotlin Landmark detection using Android Firebase ML Kit.mp4 (45.3 MB)
    7. Object Detection
    • 1. Building Object detector Android Application using Firebase ML kit.mp4 (115.1 MB)
    • 2. Writing object detector code using Android Firebase ML Kit.mp4 (51.7 MB)
    • 3. Testing Android object detection Application.mp4 (60.7 MB)
    8. AutoML and Stones Recognizer
    • 1. Creating Android and Firebase Project.mp4 (23.1 MB)
    • 2. Android Firebase ML Kit Arranging our dataset.mp4 (19.6 MB)
    • 3. Android Firebase ML Kit Training model using AutoML.mp4 (34.0 MB)
    • 4. Android Firebase ML Kit Downloading and evaluating model.mp4 (25.2 MB)
    • 5. Android Firebase ML Kit Adding Model and Creating UI.mp4 (58.4 MB)
    • 6. Android Firebase ML Kit Writing Recognizer Code.mp4 (57.2 MB)
    9. Project
    • 1. Creating Project UI.mp4 (112.5 MB)
    • 2. Initializing UI Elements.mp4 (39.6 MB)
    • 3. Getting all phone images.mp4 (91.8 MB)
    • 4. Writing detector code.mp4 (117.9 MB)
    • 5. Processing all images.mp4 (51.4 MB)
    • 6. Creating Adapter for Recyclerview.mp4 (95.6 MB)
    • Bonus Resources.txt (0.3 KB)

Description

Android & Firebase ML Kit in Java / Kotlin

Duration: 3h 58m | Video: .MP4, 1280x720 30 fps | Audio: AAC, 44.1 kHz, 2ch | Size: 2.47 GB
Genre: eLearning | Language: English
Smart Android app development
What you'll 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
Requirements:
Very basic Knowledge of Android Development with java
Description:
Requirements
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
Text Recognition Android Application
Android Application to Translate between Languages
Language Detection Application
Face Detection Application
Barcode Scanner Android Application
Object Detection Android App
Landmark Recognition Application
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\

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[ FreeCourseWeb ] Udemy - Android & Firebase ML Kit in Java - Kotlin

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