Mastering Machine Learning with MATLAB [Video]

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Mastering Machine Learning with MATLAB [Video]

Giuseppe Ciaburro

Raise your Machine Learning skills with MATLAB

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Video Details

ISBN 139781788998130
Course Length2 hours and 10 minutes

Video Description

MATLAB is the language of choice for many researchers and mathematics experts for Machine Learning. This video course will help you build a foundation in Machine Learning using MATLAB. You’ll start by performing data fitting, pattern recognition, and clustering analysis. Then, you’ll explore feature selection and extraction techniques for dimensionality reduction for performance improvement. Finally, you will learn to put it all together through real-world cases covering major Machine Learning algorithms and will now be an expert in performing Machine Learning with MATLAB.

Style and Approach

The video takes a very comprehensive approach to enhance your understanding of Machine Learning using MATLAB. Numerous real-world examples and use cases are included in the video to help you grasp the required concepts quickly and apply them easily in your day-to-day work.

Table of Contents

Pattern Recognition through Classification Algorithms
The Course Overview
Predicting a Response by Decision Trees
Probabilistic Classification Algorithms ? Naive Bayes
Describing Differences by Discriminant Analysis
Find Similarities Using Nearest Neighbor Classifiers
Classification Learner App
Identifying Groups of Data Using Clustering Methods
Introduction to Clustering
Hierarchical Clustering
Partitioning-Based Clustering Methods ? K-means Algorithm
Partitioning around the Actual Center ? K-medoidsClustering
Clustering Using Gaussian Mixture Models
Simulation of Human Thinking – Artificial Neural Networks
Getting Started with Neural Networks
Basic Elements of a Neural Network
Neural Network Toolbox
Exploring Neural Network Start GUI
Data Fitting with Neural Networks
Improving the Performance with Dimensionality Reduction
Feature Selection
Feature Extraction

What You Will Learn

  • Discover different ways to transform data using SAS XPORT, import, and export tools.
  • Discover the basics of classification methods and how to implement the Naive Bayes algorithm and Decision Trees in the MATLAB environment.
  • Use clustering methods such as hierarchical clustering to group data using similarity measures.
  • Perform data fitting, pattern recognition, and clustering analysis with the help of the MATLAB Neural Network Toolbox.
  • Use feature selection and extraction for dimensionality reduction, leading to improved performance.

Authors

Table of Contents

Pattern Recognition through Classification Algorithms
The Course Overview
Predicting a Response by Decision Trees
Probabilistic Classification Algorithms ? Naive Bayes
Describing Differences by Discriminant Analysis
Find Similarities Using Nearest Neighbor Classifiers
Classification Learner App
Identifying Groups of Data Using Clustering Methods
Introduction to Clustering
Hierarchical Clustering
Partitioning-Based Clustering Methods ? K-means Algorithm
Partitioning around the Actual Center ? K-medoidsClustering
Clustering Using Gaussian Mixture Models
Simulation of Human Thinking – Artificial Neural Networks
Getting Started with Neural Networks
Basic Elements of a Neural Network
Neural Network Toolbox
Exploring Neural Network Start GUI
Data Fitting with Neural Networks
Improving the Performance with Dimensionality Reduction
Feature Selection
Feature Extraction

Video Details

ISBN 139781788998130
Course Length2 hours and 10 minutes
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