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Building a simple Neural Network using Deep Learning
Well, this article has been long awaited and much requested so here it is :)).
Before we get started we must understand two fundamental concepts, the what and the why of neural networks and deep learning.
What is deep learning?
At this point almost all of us have heard of this out-of-touch concept of deep learning. But maybe it isn’t that out of touch after all. Deep learning has become highly practical and popular among data science practitioners and it is now used in a variety of fields thanks to recent advancements in data storage, computational ability and new algorithms.
But what is it?
Quite simply, deep learning refers to a neural network.
Your next question must be what is a neural network?
Well, a neural network in it’s most simple terms is just a function that fits and processes some data. This data-processing structure is called a neuron.
The function itself can be anything, linear or sigmoid, but obviously a single neuron has no advantage over the average traditional machine learning algorithm.
This is where the neural network begins to mimic our brain. The network combines multiple neurons. Neurons act as the building block of the network…
