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What is a neural network?
The term deep learning refers to training neural networks. In this post I’d like to provide some basic intuitions on neural networks.
    Let us consider an example where we are trying to predict the price of a house given its size. Let’s say we have a dataset with size of the houses and their corresponding price and we want to fit a function to predict the price of the house as a function of its size. In Linear Regression we try to draw a straight line to the available dataset.

    But we know that the straight line can eventually be negative whereas the price of a house is always greater than zero. So, we try to bend the curve so that it ends at 0. We can think of the function we just fit as a simple neural network where we have a node (neuron) with input as size of the house and output as price. The function is called RECTIFIED LINEAR UNIT (RELU).     A larger neural network can be formed by stacking all the single neurons. Let us extend the housing price …

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