Android ML - Train Tensorflow Lite Models for Android Apps

Description

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

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 In this course, you will learn to train your custom machine-learning models for Android and build smart Android Applications.

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 delve into the world of deep learning and artificial neural networks, which will serve as the foundation for training our regression models in 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 regression 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

Course Highlights:

1. Training Your First Regression Model:

   • Harness TensorFlow and Python to create a simple regression model

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

   • Learn to integrate the regression model into Android apps

2. Fuel Efficiency Prediction:

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

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

3. House Price Prediction in Android:

   • Master the art of training regression models on substantial datasets

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

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

• Train advanced regression models for accurate predictions

• Seamlessly integrate regression models into your Android applications

• Analyze and use existing regression models effectively within the Android ecosystem

Who Should Enroll:

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

• Enthusiasts seeking to bridge the gap between Machine Learning and mobile app development

• Data aficionados interested in harnessing the potential of data for real-world applications

Step into the World of Android and Predictive Modeling: Join us on this exciting journey and unlock the potential of Android and Linear Regression. 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 predictive modeling!

What You Will Learn!

• Train Machine Learning models for Android Applications
• Analysing & using advance regression models in Android Applications
• Train a machine learning model and build a house price prediction Android Application
• Train a machine learning model and build a fuel price prediction Android Application
• Integrate Machine Learning models in Android Applications
• Use of Tensorflow Lite models in Android
• Train Any Prediction Model & use it in Android Applications
• Data Collection & Preprocessing for model training for Android App Development
• Basics of Machine Learning & Deep Learning for Android App Development
• Understand the working of artificial neural networks for model training
• Basic syntax of python programming language
• Use of data science libraries like numpy, pandas and matplotlib

Who Should Attend!

• Beginner Android Developer who want to build Machine Learning based Android Applications
• Aspiring Android developers eager to add predictive 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

TAKE THIS COURSE