Getting Started with MATLAB Machine Learning
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Online
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Course
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Methodology
Online
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Different dates available
Easily extract patterns and knowledge from your data using MATLABMATLAB 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 AuthorGiuseppe 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), working with e-learning as an author
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About this course
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
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Course programme
- Perform the math task and assigns the result to the ans variable
- Create two variables and save the result in a third variable
- Specify row and column to select the element in the first row and second column
- Import data programmatically
- Read mixed strings and numbers
- Examine the individual entries
- Export data from MATLAB in .csv files
- Use the imwrite() function to import an image in MATLAB
- Use the audioread() function to import audio files
- Use the cell array construction operator to create a cell array
- Create a bar graph of the first customer data
- Create a table from variables in the MATLAB workspace
- Perform the math task and assigns the result to the ans variable
- Create two variables and save the result in a third variable
- Specify row and column to select the element in the first row and second column
- Import data programmatically
- Read mixed strings and numbers
- Examine the individual entries
- Export data from MATLAB in .csv files
- Use the imwrite() function to import an image in MATLAB
- Use the audioread() function to import audio files
- Use the cell array construction operator to create a cell array
- Create a bar graph of the first customer data
- Create a table from variables in the MATLAB workspace
- Perform the math task and assigns the result to the ans variable
- Create two variables and save the result in a third variable
- Specify row and column to select the element in the first row and second column
- Perform the math task and assigns the result to the ans variable
- Create two variables and save the result in a third variable
- Specify row and column to select the element in the first row and second column
- Perform the math task and assigns the result to the ans variable
- Create two variables and save the result in a third variable
- Specify row and column to select the element in the first row and second column
- Perform the math task and assigns the result to the ans variable
- Create two variables and save the result in a third variable
- Specify row and column to select the element in the first row and second column
- Perform the math task and assigns the result to the ans variable
- Create two variables and save the result in a third variable
- Specify row and column to select the element in the first row and second column
- Perform the math task and assigns the result to the ans variable
- Create two variables and save the result in a third variable
- Specify row and column to select the element in the first row and second column
- Import data programmatically
- Read mixed strings and numbers
- Examine the individual entries
- Import data programmatically
- Read mixed strings and numbers
- Examine the individual entries
- Import data programmatically
- Read mixed strings and numbers
- Examine the individual entries
- Import data programmatically
- Read mixed strings and numbers
- Examine the individual entries
- Import data programmatically
- Read mixed strings and numbers
- Examine the individual entries
- Import data programmatically
- Read mixed strings and numbers
- Examine the individual entries
- Export data from MATLAB in .csv files
- Use the imwrite() function to import an image in MATLAB
- Use the audioread() function to import audio files
- Export data from MATLAB in .csv files
- Use the imwrite() function to import an image in MATLAB
- Use the audioread() function to import audio files
- Export data from MATLAB in .csv files
- Use the imwrite() function to import an image in MATLAB
- Use the audioread() function to import audio files
- Export data from MATLAB in .csv files
- Use the imwrite() function to import an image in MATLAB
- Use the audioread() function to import audio files
- Export data from MATLAB in .csv files
- Use the imwrite() function to import an image in MATLAB
- Use the audioread() function to import audio files
- Export data from MATLAB in .csv files
- Use the imwrite() function to import an image in MATLAB
- Use the audioread() function to import audio files
- Use the cell array construction operator to create a cell array
- Create a bar graph of the first customer data
- Create a table from variables in the MATLAB workspace
- Use the cell array construction operator to create a cell array
- Create a bar graph of the first customer data
- Create a table from variables in the MATLAB workspace
- Use the cell array construction operator to create a cell array
- Create a bar graph of the first customer data
- Create a table from variables in the MATLAB workspace
- Use the cell array construction operator to create a cell array
- Create a bar graph of the first customer data
- Create a table from variables in the MATLAB workspace
- Use the cell array construction operator to create a cell array
- Create a bar graph of the first customer data
- Create a table from variables in the MATLAB workspace
- Use the cell array construction operator to create a cell array
- Create a bar graph of the first customer data
- Create a table from variables in the MATLAB workspace
Additional information
Getting Started with MATLAB Machine Learning
