Artificial Neural Network and Machine Learning using MATLAB Free Tutorial Download
What you’ll 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
Basics of Mathematics
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.
Who this course is for:
- 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