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Machine Learning Classification Algorithms using MATLAB

Machine Learning Classification Algorithms using MATLAB

Machine Learning Classification Algorithms using MATLAB

Original price was: $199.Current price is: $48.

In stock

Original price was: $199.Current price is: $48.

Machine Learning Classification Algorithms using MATLAB
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Description

Machine Learning Classification Algorithms using MATLAB

Machine Learning Classification Algorithms using MATLAB

Learn
  • Use machines learning algorithms confidently in MALTAB
  • Build classification learning models and customize them based on the datasets
  • Compare the performance of different classification algorithms
  • Learn the intuition behind classification algorithms
  • Create automatically generated reports for sharing your analysis results with friends and colleague
About 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 Output 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 essential 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 Output Codes
Segment 10: Classification with Ensembles
Segment 11: Validation Methods
Segment 12: Evaluating Performance

Style and ApproachThis course is really good for a beginner. It will help you to start from the ground up and move on to more complicated areas. You receive knowledge from a Ph.D. in Computer science (machine learning) with over 10 years of teaching and research experience,

Features
  • You can confidently implement machine learning algorithms using MATLAB.
  • You can perform meaningful analysis on the data.

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