Machine Learning Classification Algorithms using MATLAB

Simpliv

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Online

£ 10 + VAT

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Description

  • Type

    Course

  • Methodology

    Online

  • Start date

    Different dates available

This course is for you If you are being fascinated by the field of Machine Learning?Basic Course Description This course is designed to cover one of the most interesting areas of machine learning called classification. I will take you step-by-step in this course and will first cover the basics of MATLAB. Following that we will look into the details of how to use different machine learning algorithms using MATLAB. Specifically, we will be looking at the MATLAB toolbox called statistic and machine learning toolbox.We will implement some of the most commonly used classification algorithms such as K-Nearest Neighbor, Naive Bayes, Discriminant Analysis, Decision Tress, Support Vector Machines, Error Correcting Ouput Codes and Ensembles. Following that we will be looking at how to cross validate these models and how to evaluate their performances. Intuition into the classification algorithms is also included so that a person with no mathematical background can still comprehend the esesential ideas. The following are the course outlines.Segment 1: Instructor and Course Introduction
Segment 2: MATLAB Crash Course
Segment 3: Grabbing and Importing Dataset
Segment 4: K-Nearest Neighbor
Segment 5: Naive Bayes
Segment 6: Decision Trees
Segment 7: Discriminant Analysis
Segment 8: Support Vector Machines
Segment 9: Error Correcting Ouput Codes
Segment 10: Classification with Ensembles
Segment 11: Validation Methods
Segment 12: Evaluating PerformanceAt the end of this course,  You can confidently implement machine learning algorithms using MATLAB
You can perform meaningful analysis on the dataStudent Testimonials!
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This is the second Simpliv class on Matlab I've taken. Already, a couple important concepts have been discussed that weren't discussed in the previous course. I'm glad the instructor is comparing Matlab to Excel, which is the tool I've been using and have been frustrated with. This course is a little more advanced than the previous course I took...

Facilities

Location

Start date

Online

Start date

Different dates availableEnrolment now open

About this course

Use machines learning algorithms confidently in MALTAB
Build classification learning models and customize them based on the datasets
Compare the performance of diffferent classification algorithms
Learn the intuition behind classification algorithms
Create automatically generated reports for sharing your analysis results with friends and colleague

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This centre's achievements

2021

All courses are up to date

The average rating is higher than 3.7

More than 50 reviews in the last 12 months

This centre has featured on Emagister for 6 years

Subjects

  • Algorithms
  • Application
  • Information Systems
  • Information Systems management
  • Systems
  • IT
  • IT Management
  • Management
  • Computing
  • Engineering

Course programme

Instructor and Course Introduction 4 lectures 07:57 Applications of Machine Learning Why use MATLAB for Machine Learning Meet Your Instructor Course Outlines Instructor and Course Introduction 4 lectures 07:57 Applications of Machine Learning Why use MATLAB for Machine Learning Meet Your Instructor Course Outlines Applications of Machine Learning Applications of Machine Learning Applications of Machine Learning Applications of Machine Learning Why use MATLAB for Machine Learning Why use MATLAB for Machine Learning Why use MATLAB for Machine Learning Why use MATLAB for Machine Learning Meet Your Instructor Meet Your Instructor Meet Your Instructor Meet Your Instructor Course Outlines Course Outlines Course Outlines Course Outlines MATLAB Crash Course 3 lectures 21:54 MATLAB Pricing and Online Resources MATLAB GUI Some common Operations MATLAB Crash Course 3 lectures 21:54 MATLAB Pricing and Online Resources MATLAB GUI Some common Operations MATLAB Pricing and Online Resources MATLAB Pricing and Online Resources MATLAB Pricing and Online Resources MATLAB Pricing and Online Resources MATLAB GUI MATLAB GUI MATLAB GUI MATLAB GUI Some common Operations Some common Operations Some common Operations Some common Operations Grabbing and Importing a Dataset 4 lectures 29:34 Data Types that We May Encounter Grabbing a dataset Importing Data into MATLAB Understanding the Table Data Type Grabbing and Importing a Dataset 4 lectures 29:34 Data Types that We May Encounter Grabbing a dataset Importing Data into MATLAB Understanding the Table Data Type Data Types that We May Encounter Data Types that We May Encounter Data Types that We May Encounter Data Types that We May Encounter Grabbing a dataset Grabbing a dataset Grabbing a dataset Grabbing a dataset Importing Data into MATLAB Importing Data into MATLAB Importing Data into MATLAB Importing Data into MATLAB Understanding the Table Data Type Understanding the Table Data Type Understanding the Table Data Type Understanding the Table Data Type K-Nearest Neighbor 7 lectures 56:48 Nearest Neighbor Intuition Nearest Neighbor in MATLAB Learning KNN model with features subset and with non-numeric data Dealing with scalling issue and copying a learned model (4) Types of Properties (5) Building a model with subset of classes, missing values and instances weights Properties of KNN K-Nearest Neighbor 7 lectures 56:48 Nearest Neighbor Intuition Nearest Neighbor in MATLAB Learning KNN model with features subset and with non-numeric data Dealing with scalling issue and copying a learned model (4) Types of Properties (5) Building a model with subset of classes, missing values and instances weights Properties of KNN Nearest Neighbor Intuition Nearest Neighbor Intuition Nearest Neighbor Intuition Nearest Neighbor Intuition Nearest Neighbor in MATLAB Nearest Neighbor in MATLAB Nearest Neighbor in MATLAB Nearest Neighbor in MATLAB Learning KNN model with features subset and with non-numeric data Learning KNN model with features subset and with non-numeric data Learning KNN model with features subset and with non-numeric data Learning KNN model with features subset and with non-numeric data Dealing with scalling issue and copying a learned model (4) Dealing with scalling issue and copying a learned model (4) Dealing with scalling issue and copying a learned model (4) Dealing with scalling issue and copying a learned model (4) Types of Properties (5) Types of Properties (5) Types of Properties (5) Types of Properties (5) Building a model with subset of classes, missing values and instances weights Building a model with subset of classes, missing values and instances weights Building a model with subset of classes, missing values and instances weights Building a model with subset of classes, missing values and instances weights Properties of KNN Properties of KNN Properties of KNN Properties of KNN Naive Bayes 4 lectures 35:41 Intuition of Naive Bayesain Classification Naive Bayes in MATLAB Building a model with categorical data A Final note on Naive Bayesain Model Naive Bayes 4 lectures 35:41 Intuition of Naive Bayesain Classification Naive Bayes in MATLAB Building a model with categorical data A Final note on Naive Bayesain Model Intuition of Naive Bayesain Classification Intuition of Naive Bayesain Classification Intuition of Naive Bayesain Classification Intuition of Naive Bayesain Classification Naive Bayes in MATLAB Naive Bayes in MATLAB Naive Bayes in MATLAB Naive Bayes in MATLAB Building a model with categorical data Building a model with categorical data Building a model with categorical data Building a model with categorical data A Final note on Naive Bayesain Model A Final note on Naive Bayesain Model A Final note on Naive Bayesain Model A Final note on Naive Bayesain Model Decision Trees 5 lectures 45:47 Intuition of Decision Trees Decision Trees in MATLAB Properties of the Decision Trees Node Related Properties of Decision Trees Properties at the Classifier Built Time Decision Trees etermining the classification loss Determining the classification loss ...

Additional information

Just basic high level math

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Machine Learning Classification Algorithms using MATLAB

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