Train Image Classification Models, build Android Kotlin Apps
- Description
- Curriculum
- FAQ
- Reviews
Unlock the full potential of mobile app development with our comprehensive course on training custom image Recognition models and integrating them into Android applications. This course is designed to guide you from the basics of machine learning and deep learning to creating sophisticated, real-time image recognition apps in Android Kotlin.
What You Will Learn:
-
Introduction to Machine Learning and Deep Learning: Start with the foundational concepts of machine learning, deep learning, and image Recognition to build a strong base for your journey.
-
Dataset Collection: Learn effective methods to collect and prepare datasets for training your image Recognition models.
-
Model Training Approaches: Train image Recognition models using two powerful approaches:
-
Teachable Machine: A user-friendly platform to create custom models.
-
Transfer Learning: Advanced technique to leverage pre-trained models for better accuracy and efficiency.
-
-
Tensorflow Lite Conversion: Convert your trained models into TensorFlow Lite format, making them compatible with mobile applications.
-
Android Integration: Seamlessly integrate your models into Android apps:
-
Image Recognition : Choose or capture images in Android and use your models for accurate image recognition.
-
Real-Time Camera Footage: Display live camera footage in Android, pass frames to your models, and build real-time, intelligent mobile apps.
-
Projects Included:
-
Fruit and Vegetable Classification Model: Create an app that identifies different fruits and vegetables.
-
Brain Tumor Classification Model: Develop a model to classify brain tumor images.
-
Flower Classification Model: Build a system to recognize various types of flowers.
By the end of this course, you’ll be able to:
-
Train custom image Recognition models tailored to your specific needs.
-
Seamlessly integrate your models into Android applications built with Kotlin.
-
Craft intelligent mobile apps that leverage real-time image recognition functionalities.
So join us to become proficient in Android app development and create cutting-edge mobile apps with image and video recognition capabilities using Kotlin.
Enroll now and start your journey towards mastering Android and Image Recognition .
-
3
What is Machine Learning -
4
Supervised Machine Learning
-
5
Regression and Classification
-
6
Unsupervised Machine Learning & Reinforcement Learning
-
7
Deep Learning and Neural Network Introduction
-
8
Neural Network Example
-
9
Working of Neural Networks for Image Classification
-
10
Basic Concepts of Machine Learning
-
15
Section Introduction
-
16
Exploring Teachable Machine and Uploading Dataset for Model Training
-
17
Training, Testing and Converting Model into Tensorflow Lite
-
18
Attaching Metadata with Trained Tensorflow Lite Models
-
19
Google Colab Introduction
-
20
Attaching Metadata and Downloading Ready to Use Model
-
21
Transfer Learning Introduction
-
22
Google Colab Introduction
-
23
Installing and Importing Libraries for Model Training
-
24
Uploading Dataset and Connecting Google Drive
-
25
Dividing dataset into train test and validation parts
-
26
Training Custom Image Classification Model
-
27
Testing the model and Converting it to Tensorflow Lite Format
