Artificial Neural Network and Machine Learning using MATLAB
Artificial Neural Network and Machine Learning using MATLAB, available at $59.99, has an average rating of 3.73, with 52 lectures, based on 390 reviews, and has 1423 subscribers.
You will learn about 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 This course is ideal for individuals who are Anyone with passion for learning! or Anyone who wants to develop a Neural Network with no programming skills! or Students who want to learn and apply machine learning for their projects. or Professionals in the field of Electronic, Computer, IT and Industry. or Researchers who want to explore and conduct a research with Machine Learning techniques. or Any business owner who wants to understand how to leverage the Machine Learning in their business or Anyone who is looking for salary growth and new opportunities in the field of Data Science and Machine Learning It is particularly useful for Anyone with passion for learning! or Anyone who wants to develop a Neural Network with no programming skills! or Students who want to learn and apply machine learning for their projects. or Professionals in the field of Electronic, Computer, IT and Industry. or Researchers who want to explore and conduct a research with Machine Learning techniques. or Any business owner who wants to understand how to leverage the Machine Learning in their business or Anyone who is looking for salary growth and new opportunities in the field of Data Science and Machine Learning.
Enroll now: Artificial Neural Network and Machine Learning using MATLAB
Summary
Title: Artificial Neural Network and Machine Learning using MATLAB
Price: $59.99
Average Rating: 3.73
Number of Lectures: 52
Number of Published Lectures: 52
Number of Curriculum Items: 52
Number of Published Curriculum Objects: 52
Original Price: $199.99
Quality Status: approved
Status: Live
What You Will Learn
- 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
Who Should Attend
- Anyone with passion for learning!
- Anyone who wants to develop a Neural Network with no programming skills!
- Students who want to learn and apply machine learning for their projects.
- Professionals in the field of Electronic, Computer, IT and Industry.
- Researchers who want to explore and conduct a research with Machine Learning techniques.
- Any business owner who wants to understand how to leverage the Machine Learning in their business
- Anyone who is looking for salary growth and new opportunities in the field of Data Science and Machine Learning
Target Audiences
- Anyone with passion for learning!
- Anyone who wants to develop a Neural Network with no programming skills!
- Students who want to learn and apply machine learning for their projects.
- Professionals in the field of Electronic, Computer, IT and Industry.
- Researchers who want to explore and conduct a research with Machine Learning techniques.
- Any business owner who wants to understand how to leverage the Machine Learning in their business
- Anyone who is looking for salary growth and new opportunities in the field of Data Science and Machine Learning
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.
Course Curriculum
Chapter 1: Introduction
Lecture 1: Introduction
Chapter 2: Artificial Intelligence and Machine Learning
Lecture 1: History of A.I.
Lecture 2: Artificial Intelligence
Lecture 3: Machine Learning
Lecture 4: Learning Methods
Lecture 5: Supervised Learning
Lecture 6: Unsupervised Learning
Lecture 7: Reinforcement Learning
Chapter 3: Fundamentals of Artificial Neural Network
Lecture 1: Biological Model of Neural Network
Lecture 2: How our Brain makes decisions
Lecture 3: Classification theory
Lecture 4: What is Artificial Neuron
Lecture 5: Combinational Logic Gate: AND
Lecture 6: Logical Disjunction Gate: OR
Lecture 7: Artificial Neuron Model
Lecture 8: Exclusive Logical Gate: XOR
Lecture 9: Complementary Lecture on "Exclusive Logical Gate: XOR"
Lecture 10: Multilayer Perceptron Concepts
Lecture 11: Mathematical Model of Net function
Lecture 12: Mathematical Model of MPL
Lecture 13: Hardware Implementation of a Neuron
Lecture 14: MLP Structure
Lecture 15: Neural Network's Logic
Lecture 16: Calculating Mean Square Error
Lecture 17: Optimization Methods
Lecture 18: Techniques of Neural Networks
Lecture 19: Neural Network Architectures
Chapter 4: MATLAB: Neural Net Fitting Tool
Lecture 1: MATLAB overview
Lecture 2: Function Approximation Example
Lecture 3: Generate Data in MATLAB
Lecture 4: Data Selection
Lecture 5: Validation and Test Data
Lecture 6: Train Network
Lecture 7: Plots
Lecture 8: Retrain the Neural Network
Lecture 9: Effect of increasing the number of samples on NN
Lecture 10: Activation Function
Lecture 11: Affect of Neurons in Hidden Layer on NN
Lecture 12: Calculate Maximum Number of Neurons per Layer
Chapter 5: MATLAB: Scripts
Lecture 1: Save Data to Work Space
Lecture 2: Create Simple Script
Lecture 3: Create Advanced Script
Chapter 6: MATLAB: Modified Advance Script
Lecture 1: Fitting Network
Lecture 2: Train Function
Lecture 3: Performance Function
Lecture 4: Train Parameters
Lecture 5: Recalculating Training, Validation and Test Performance
Lecture 6: Modify Plots
Chapter 7: MATLAB: Engine Data Set (Multiple Targets)
Lecture 1: Create a NN for Engine Data Set
Lecture 2: Create a Function
Lecture 3: Two Targets in the Same NN
Lecture 4: Types of Data
Instructors
-
Nastaran Reza Nazar Zadeh
MS Computer Engineer
Rating Distribution
- 1 stars: 8 votes
- 2 stars: 12 votes
- 3 stars: 44 votes
- 4 stars: 136 votes
- 5 stars: 190 votes
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