Create your Neural Network from Scratch

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.