Students, scientists, and developers have the tendency to treat neural
networks like a magic black box. For those that want a free workshop
and course on the understanding of neural networks and how to program
this from scratch- this is for you.
In this 2.5 hour highly interactive workshop you will learn how to
program an aspect of the introductory neural network. The feedforward
algorithm. You will also be given detailed guidelines after the
workshop how to continue to learn how to optimize your algorithm and
add the essential aspects like the backpropogation algorithm.We cut
down the concepts to a minimum. So this will provide introductory
theory and practical hand in hand for an engaging period of full
throttled learning. The neural network itself will be simplied to
include only one dimension in the hidden layer so that only a basic
understanding of linear algebra will be required. You will learn why
an activation function is used and how that atually was inspired by
your very own biological neurons firing whenever you make decisions.
Who should attend?
Our neural network course was developed for junior data scientists or
curious learners from this field seeking a better understanding and
knowledge of basic principles of neural networks and how to program
them.
Course objectives
Gain a basic understanding of neural networks, how they work and how
they can be applied.
Learn to program a class in python
Learn what a matrix is and why we use it in neural networks
Learn to program a matrix and how to perform matrix multiplications
Know what a sigmoid function is and how it relates to the activation
function similar to biological neurons
Learn to program a feedforward algorithm given a matrix of inputs,
hidden layers, weights and a sigmoid function
Be able to build a simple aspect of a neural network and receive a 1
month free trial to Diggit which contains a course as to how you can
fully build a neural network from scratch.
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20/12/2018 Last update