AI Byte-Sized Series: Linear Regression Model
- Created By raju2006
- Last Updated December 27th, 2023
- Overview
- Prerequisites
- Audience
- Audience
- Curriculum
Session Description:
Learn how to kickstart your machine learning journey with this beginner-friendly guide on applying the linear regression algorithm. Build predictive models easily using step-by-step instructions and practical examples.
Setup:
Because this is an abbreviated session, attendees MUST install Anaconda software https://www.anaconda.com/ and have a basic understanding of using Jupyter Notebook."
Course Code/Duration:
BDT77 / 90 Minutes
Learning Objectives:
Learn about the intuition about Linear Regression algorithm in machine learning for Univariate and Multi-variate data. We will then build a linear regression algorithm to do the following:
- Articulate the core concepts of linear regression for both univariate and multi-variate data.
- Develop a strong intuition about how the regression line captures the relationship between variables.
- Build and train linear regression models using real-world datasets.
- Evaluate model performance using essential metrics, enabling you to gauge the accuracy and reliability of your predictions.
- Learn basic understanding of python language, pandas library and understanding of how to use Juypter Notebook.
- This session is designed for anyone who is familiar with basic steps involved in machine learning and are familiar with tools involved in building machine learning models.
- This session is designed for anyone who is familiar with basic steps involved in machine learning and are familiar with tools involved in building machine learning models.
Course Outline:
- Definition of linear regression model
- Importance of linear regression model in machine learning.
- Preparing data for linear regression
- Training and testing a linear regression model
- Evaluating model performance
- Metrics for evaluating model performance.
The curriculum is empty
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