Android 15 & ML - Train Tensorflow Lite Models for Android

Description

Do you want to train different Machine Learning models and build smart Android applications then Welcome to this course.

In this course, you will learn to train powerful

• Image Classification

• Object Detection

• Linear Regression

model in python from scratch. After that you will learn to

• Use your custom trained Machine Learning Models in Android

• Use existing tensorflow lite models in Android Apps

Regression

Regression is one of the fundamental techniques in Machine Learning which can be used for countless applications. Like you can train Machine Learning models using regression

• to predict the price of the house

• to predict the Fuel Efficiency of vehicles

• to recommend drug doses for medical conditions

• to recommend fertilizer in agriculture

• to suggest exercises for improvement in player performance

and so on. So Inside this course, you will learn to train your custom linear regression models in Tensorflow Lite format and build smart Android Applications.

Image Classification & Applications

Image classification is the process of recognizing different entities or things in an image or video. You can recognize animals, plants, diseases, food, activities, colors, things, fictional characters, drinks, etc with image recognition.

• In e-commerce applications image classification can be used to categorize products based on their visual features, So it is used to organize products into categories for easy browsing.

• Image classification can be used to power visual search in mobile apps, so users can take a picture of an object and then find similar items for sale.

• Image classification can be used in medical apps to diagnose disease based on medical images, such as X-rays or CT scans.

• We can use image classification to build countless recognition applications for performing number of tasks, like we can train a model and build applications to recognize

  • Different Breeds of dogs

  • Different Types of plants

  • Different Species of Animals

  • Different kind of precious stones

Image Classification & Applications

Object detection is a powerful computer vision technique that can accurately identify and pinpoint the location of various objects within images or videos. By recognizing objects like cars, people, and animals, this technology empowers applications such as security surveillance, autonomous vehicles, and smartphone apps that can identify objects through the camera lens.

Key Applications:

• Autonomous Vehicles: Cars equipped with object detection can safely navigate roads, avoid collisions, and enhance driver assistance systems.

• Surveillance Systems: Security cameras can identify individuals, track suspicious activity, and detect intrusions.

• Retail: Stores can monitor customer behavior, manage inventory, and prevent theft.

• Healthcare: Medical imaging systems can detect anomalies like tumors and fractures.

• Agriculture: Farmers can monitor crops, livestock, and detect pests or diseases.

• Manufacturing: Quality control and automation can be improved through object inspection and robotic guidance.

• Sports Analytics: Tracking player movements and equipment can enhance performance analysis and fan experience.

• Environmental Monitoring: Wildlife conservation and habitat protection can benefit from object detection.

• Smart Cities: Traffic management, public space monitoring, and waste management can be optimized.

I'm Muhammad Hamza Asif, and in this course, we'll embark on a journey to combine the power of predictive modeling with the flexibility of Android app development. Whether you're a seasoned Android developer or new to the scene, this course has something valuable to offer you

Course Overview: We'll begin by exploring the basics of Machine Learning and its various types, and then dive into the world of deep learning and artificial neural networks, which will serve as the foundation for training our machine learning models for Android.

The Android-ML Fusion: After grasping the core concepts, we'll bridge the gap between Android and Machine Learning. To do this, we'll kickstart our journey with Python programming, a versatile language that will pave the way for our machine learning model training

Unlocking Data's Power: To prepare and analyze our datasets effectively, we'll dive into essential data science libraries like NumPy, Pandas, and Matplotlib. These powerful tools will equip you to harness data's potential for accurate predictions.

Tensorflow for Mobile: Next, we'll immerse ourselves in the world of TensorFlow, a library that not only supports model training using neural networks but also caters to mobile devices, including Android

Regression Models Training

1. Training Your First Machine Learning Model:

   • Harness TensorFlow and Python to create a simple linear regression model

   • Convert the model into TFLite format, making it compatible with Android

   • Learn to integrate the tflite model into Android apps for Android

2. Fuel Efficiency Prediction:

   • Apply your knowledge to a real-world problem by predicting automobile fuel efficiency

   • Seamlessly integrate the model into a Android app for an intuitive fuel efficiency prediction experience

3. House Price Prediction in Android:

   • Master the art of training machine learning models on substantial datasets

   • Utilize the trained model within your Android app to predict house prices confidently

Computer Vision Model Training

1. Image Classification in Android:

   • Collect and process dataset for model training

   • Train image classification models on custom datasets with Teachable Machine

   • Train image classification models on custom datasets with Transfer Learning

   • Use image classification models in Android with both images and live camera footage

2. Object Detection in Android

   • Collect and Annotate Dataset for Object Detection Model Training

   • Train Object Detection Models

   • Use object detection models in Android with Images & Videos

   
   

The Android Advantage: By the end of this course, you'll be equipped to:

• Train advanced machine learning models for accurate predictions

• Seamlessly integrate tflite models into your Android applications

• Analyze and use existing regression & vision (ML) models effectively within the Android ecosystem

Who Should Enroll:

• Aspiring Android developers eager to add predictive modeling to their skillset

• Beginner Android developer with very little knowledge of mobile app development

• Intermediate Android developer wanted to build a powerful Machine Learning-based application

• Experienced Android developers wanted to use Machine Learning models inside their applications.

Step into the World of Android and Machine Learning: Join us on this exciting journey and unlock the potential of Android and Machine Learning. By the end of the course, you'll be ready to develop Android applications that not only look great but also make informed, data-driven decisions.

Enroll now and embrace the fusion of Android and Machine Learning!

Who this course is for:

• Beginner Android Developers who want to train ML models and build Machine Learning based Android Applications
• Aspiring Android developers eager to add ML modeling to their skillset
• Enthusiasts seeking to bridge the gap between Machine Learning and mobile app development.
• Machine Learning Engineers looking to build real world applications with Machine Learning Models