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Deep Learning & Neural Networks in Matlab from Fundamentals

 Deep Learning & Neural Networks in Matlab from Fundamentals
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Link :  Deep Learning & Neural Networks in Matlab from Fundamentals
In this book, readers start with machine learning fundamentals. They then move on to neural networks, deep learning, and convolutional neural networks. Using a blend of fundamentals and applications, this text employs MATLAB as the underlying programming language and tool for the examples and case studies in this book. In addition, a ...
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by Eliott Wertheimer, Albert Nassar

What you'll learn
  • How neural networks emulate the brain
  • How to artificially represent neural networks
  • The biological fundamentals behind neural networks and deep learning
  • How to represent and manipulate neural networks with matrices
  • The basics behind training neural networks and the cost function
  • How to use gradient descent and learning intuition
  • The maths and calculus behind forward and back propagation
  • How to represent forward and back propagation in matrix form
  • How to write forward and back propagation algorithms
  • Understand and master the mathematics and algorithms behind deep learning and neural networks
  • The structure of the MNIST database and how to use and extract data from it
  • How to program and use the Sigmoid and Leaky Relu activation functions in MATLAB
  • How to create a Neural Network in Matlab
  • How to create Neural Network training and testing algorithms in Matlab
  • How to use the MNIST database to make a neural network able to read handwritten numbers in images

AI is omnipresent in our modern world. It is in your phone, in your laptop, in your car, in your fridge and other devices you would not dare to think of. After thousands of years of evolution, humanity has managed to create machines that can conduct specific intelligent tasks when trained properly. How? Through a process called machine learning or deep learning, by mimicking the behaviour of biological neurons through electronics and computer science. Even more than it is our present, it is our future, the key to unlocking exponential technological development and leading our societies through wonderful advancements.

As amazing as it sounds, it is not off limits to you, to the contrary!

We are both engineers, currently designing and marketing advanced ultra light electric vehicles. Albert is a Mechanical engineer specializing in advanced robotics and Eliott is an Aerospace Engineer specializing in advanced space systems with past projects completed in partnership with the European Space Agency.

The aim of this course is to teach you how to fully, and intuitively understand neural networks, from their very fundamentals. We will start from their biological inspiration through their mathematics to go all the way to creating, training and testing your own neural network on the famous MNIST database.

It is important to note that this course aims at giving you a complete and rich understanding of neural networks and AI, in order to give you the tools to create your own neural networks, whatever the project or application. We do this by taking you through the theory to then apply it on a very hands-on MATLAB project, the goal being for you to beat our own neural network's performance!
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