Udemy

Artificial Neural Network and Machine Learning using MATLAB

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  • 1,650 名學生
  • 更新於 9/2025
  • 可獲發證書
4.5
(465 個評分)
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課程資料

報名日期
全年招生
課程級別
學習模式
修業期
4 小時 26 分鐘
教學語言
英語
授課導師
Nastaran Reza Nazar Zadeh
證書
  • 可獲發
  • *證書的發放與分配,依課程提供者的政策及安排而定。
評分
4.5
(465 個評分)
1次瀏覽

課程簡介

Artificial Neural Network and Machine Learning using MATLAB

Learn to Create Neural Network with Matlab Toolbox and Easy to Follow Codes; with Comprehensive Theoretical Concepts

This course is uniquely designed to be suitable for both experienced developers seeking to make that jump to Machine learning or complete beginners who don't understand machine learning and Artificial Neural Network from the ground up.

In this course, we introduce a comprehensive training of multilayer perceptron neural networks or MLP in MATLAB, in which, in addition to reviewing the theories related to MLP neural networks, the practical implementation of this type of network in MATLAB environment is also fully covered.

MATLAB offers specialized toolboxes and functions for working with Machine Learning and Artificial Neural Networks which makes it a lot easier and faster for you to develop a NN.

At the end of this course, you'll be able to create a Neural Network for applications such as classification, clustering, pattern recognition, function approximation, control, prediction, and optimization.

課程章節

  • 7 個章節
  • 53 堂課
  • 第 1 章 Introduction
  • 第 2 章 Artificial Intelligence and Machine Learning
  • 第 3 章 Fundamentals of Artificial Neural Network
  • 第 4 章 MATLAB: Neural Net Fitting Tool
  • 第 5 章 MATLAB: Scripts
  • 第 6 章 MATLAB: Modified Advance Script
  • 第 7 章 MATLAB: Engine Data Set (Multiple Targets)

課程內容

  • Develop a multilayer perceptron neural networks or MLP in MATLAB using Toolbox
  • Apply Artificial Neural Networks in practice
  • Building Artificial Neural Network Model
  • Knowledge on Fundamentals of Machine Learning and Artificial Neural Network
  • Understand Optimization methods
  • Understand the Mathematical Model of a Neural Network
  • Understand Function approximation methodology
  • Make powerful analysis
  • Knowledge on Performance Functions
  • Knowledge on Training Methods for Machine Learning

評價

  • G
    Girolama Airò Farulla
    5.0

    I like it very much. The notions are well explained, and the examples are very effective. Highly recommended course!

  • M
    Meghana M.R
    5.0

    it is very good

  • p
    prasun choudhary
    5.0

    Please let me complete it. Till this section, everything is excellent.

  • O
    Osama Alawi
    5.0

    very valuable course

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