Artificial Neural Network and Machine Learning using MATLAB

Artificial neural networks (ANNs) and machine learning are two of the most important and rapidly developing fields in computer science. ANNs are inspired by the structure and function of the human brain, and they are used to solve a wide range of problems, including pattern recognition, classification, and prediction.

Machine learning is a field of computer science that gives computers the ability to learn without being explicitly programmed. Machine learning algorithms are used to train ANNs, and they are also used to solve a wide range of problems, including data mining, natural language processing, and image recognition.

MATLAB is a powerful software platform that can be used to develop and train ANNs. MATLAB also provides a variety of tools for machine learning algorithms.

Artificial Neural Network and Machine Learning using MATLAB Course Overview

Both experienced developers who wish to make the switch to machine learning and beginners who are unfamiliar with artificial neural networks and machine learning can benefit from this training.

This course gives thorough training in Multilayer Perceptron Neural Networks, or MLP in MATLAB, and covers both the theoretical underpinnings of these networks as well as their practical use in the MATLAB environment.

The creation of ANN is significantly facilitated and accelerated by the use of MATLAB, which offers specialized tools and functions for working with machine learning and artificial neural networks.

You will be able to build a neural network at the end of this course and use it for tasks including classification, clustering, pattern recognition, function approximation, control, prediction, and optimization.