Artificial Neural Network and Machine Learning using MATLAB 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.
What you’ll learn: Develop a multilayer perceptron neural networks or MLP in MATLAB using Toolbox + Apply Artificial Neural Networks in practiceBuilding 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.
What you’ll learn: Develop a multilayer perceptron neural networks or MLP in MATLAB using Toolbox + Apply Artificial Neural Networks in practiceBuilding 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.