Linear Regression & Python- Machine Learning for Mobile Apps

Description

Do you want to train Machine Learning Models and use them in Mobile, Web, and Desktop applications then welcome to this course. In this course, you will learn to train linear regression models and convert them into tensorflow lite format so that you can use them in mobile, desktop, and edge devices.

Regression is one of the fundamental techniques in Machine Learning which can be used for countless applications. 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.

The course will is divided into several sections

• Introduction of Machine Learning and its Types

• Basics of Deep Learning & Artificial Neural Networks

• Basic Syntax of Python Programming Language

• Data Science Libraries (Numpy, Pandas, Matplotlib)

• Tensorflow & Tensorflow Lite

• Training a simple linear regression model

• Training an advanced linear regression model to predict fuel efficiency

• Building a House Price Prediction Linear Regression Model

Instructor Intro:

My name is Muhammad Hamza Asif and I am the leading Mobile Machine Learning Instructor at Udemy. For the last five years, I am teaching the use of Machine Learning and AI in mobile applications to over 55,000 thousand students worldwide.

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 Tensorflow Lite models for mobile Applications.

Python Programming: After grasping the core concepts, we'll learn the basic syntax of 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.

Course Highlights:

1. Training Your First Linear Regression Model:

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

   • Convert the machine learning model into TFLite format, making it compatible with mobile applications

2. Fuel Efficiency Prediction:

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

   • Convert advanced linear regression models in a mobile-compatible format

3. House Price Prediction:

   • Master the art of training linear regression models on substantial datasets

   • Evaluate the machine learning model and convert it into tensorflow lite format

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

• Train advanced linear regression models for accurate predictions

• Convert machine learning models into tensorflow lite format for use in mobile & edge devices

• Understand the basics of Machine Learning, Deep Learning, Regression, Linear Regression, Classification, Python, Numpy, Pandas, Matplotlib, Tensorflow and Tensorflow Lite

Who Should Enroll:

• People who are interested in data science & machine learning

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

• Aspiring developers eager to add predictive modeling / linear regression to their skillset

• People new to machine learning who would like an easy introduction to the topic

• People who wish to advance their careers by learning machine learning for mobile devices

  
  

Join us on this exciting journey and unlock the potential of Machine Learning with Linear Regression for mobile and edge devices.

TAKE THIS COURSE