Getting Started with MATLAB Machine Learning

Getting Started with MATLAB Machine Learning, available at $39.99, has an average rating of 3.35, with 10 lectures, 3 quizzes, based on 40 reviews, and has 170 subscribers.

You will learn about Learn the introductory concepts of machine learning Explore the different types of regression technique such as simple and multiple linear regression, ordinary least squares estimation, correlations, and how to apply them to your data Discover the basics of classification methods and how to implement the Naive Bayes algorithm and Decision Trees in the MATLAB environment Perform data fitting, pattern recognition, and clustering analysis with the help of the MATLAB neural network toolbox This course is ideal for individuals who are This video is for data analysts, data scientists, students, or anyone keen to get started with machine learning and build efficient data processing and predictive applications. It is particularly useful for This video is for data analysts, data scientists, students, or anyone keen to get started with machine learning and build efficient data processing and predictive applications.

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Summary

Title: Getting Started with MATLAB Machine Learning

Price: $39.99

Average Rating: 3.35

Number of Lectures: 10

Number of Quizzes: 3

Number of Published Lectures: 10

Number of Published Quizzes: 3

Number of Curriculum Items: 13

Number of Published Curriculum Objects: 13

Original Price: $109.99

Quality Status: approved

Status: Live

What You Will Learn

Learn the introductory concepts of machine learning

Explore the different types of regression technique such as simple and multiple linear regression, ordinary least squares estimation, correlations, and how to apply them to your data

Discover the basics of classification methods and how to implement the Naive Bayes algorithm and Decision Trees in the MATLAB environment

Perform data fitting, pattern recognition, and clustering analysis with the help of the MATLAB neural network toolbox

Who Should Attend

This video is for data analysts, data scientists, students, or anyone keen to get started with machine learning and build efficient data processing and predictive applications.

Target Audiences

This video is for data analysts, data scientists, students, or anyone keen to get started with machine learning and build efficient data processing and predictive applications.

MATLAB is the language of choice for many researchers and mathematics experts when it comes to machine learning. This video will help beginners build a foundation in machine learning using MATLAB. You’ll start by getting your system ready with the MATLAB environment for machine learning and you’ll see how to easily interact with the MATLAB workspace. You’ll then move on to data cleansing, mining, and analyzing various data types in machine learning and you’ll see how to display data values on a plot. Next, you’ll learn about the different types of regression technique and how to apply them to your data using the MATLAB functions. You’ll understand the basic concepts of neural networks and perform data fitting, pattern recognition, and clustering analysis. Finally, you’ll explore feature selection and extraction techniques for dimensionality reduction to improve performance. By the end of the video, you’ll have learned to put it all together via real-world use cases covering the major machine learning algorithms and will be comfortable in performing machine learning with MATLAB.

About the Author

Giuseppe Ciaburro holds a Master’s degree in chemical engineering from Università degli Studi di Napoli Federico II, and a Master’s degree in acoustic and noise control from Seconda Università degli Studi di Napoli. He works at the Built Environment Control Laboratory – Università degli Studi della Campania “Luigi Vanvitelli.”

He has over 15 years’ work experience in programming, first in the field of combustion and then in acoustics and noise control. His core programming knowledge is in Python and R, and he has extensive experience of working with MATLAB. An expert in acoustics and noise control, Giuseppe has wide experience in teaching professional computer courses (about 15 years), dealing with e-learning as an author. He has several publications to his credit: monographs, scientific journals, and thematic conferences. He is currently researching Machine Learning applications in acoustics and noise control.

Course Curriculum

Chapter 1: Importing and Organizing Data in MATLAB

Lecture 1: The Course Overview

Lecture 2: Familiarizing Yourself with the MATLAB Desktop

Lecture 3: Importing Data into MATLAB

Lecture 4: Exporting Data from MATLAB

Lecture 5: Data Organization

Chapter 2: From Data to Knowledge Discovery

Lecture 1: Data Preparation

Lecture 2: Exploratory Statistics – Numerical Measures

Lecture 3: Exploratory Visualization

Chapter 3: Finding Relationships Between Variables – Regression

Lecture 1: Searching Linear Relationships

Lecture 2: Creating a Linear Regression Model

Instructors

Packt Publishing
Tech Knowledge in Motion

Rating Distribution

1 stars: 2 votes

2 stars: 1 votes

3 stars: 12 votes

4 stars: 13 votes

5 stars: 12 votes

Frequently Asked Questions

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You can view and review the lecture materials indefinitely, like an on-demand channel.

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