Everything You Should Know about AI Neural Network

1. Everything You Should Know about AI Neural Network

2. Today, at times it seems like every other app, website, or Today, at times it seems like every other app, website, or productivity tool is using Artificial Intelligence (AI) as a productivity tool is using Artificial Intelligence (AI) as a secret ingredient in their recipe for success. If you have secret ingredient in their recipe for success. If you have spent any spent any time reading about artificial intelligence, you time reading about artificial intelligence, you shall almost certainly have heard about artificial neural shall almost certainly have heard about artificial neural networks. But exactly what is it? networks. But exactly what is it? What is Artificial Neural What is Artificial Neural Network? Network? Artificial neural networks Artificial neural networks are one of the used in machine learning. As the name ‘neural’ suggests, used in machine learning. As the name ‘neural’ suggests, they are brain they are brain- -inspired systems which are intended to inspired systems which are intended to copy the way that we humans learn. Neural networks copy the way that we humans learn. Neural networks comprise of input and output layers, together with a comprise of input and output layers, together with a hidden layer consisting of hidden layer consisting of units that transforms the input units that transforms the input into something that can be used by the output layer. into something that can be used by the output layer. Neural networks are excellent tools for identifying Neural networks are excellent tools for identifying patterns that are far too complex for a human patterns that are far too complex for a human programmer to extract and teach the machine to programmer to extract and teach the machine to recognize. recognize. are one of the primary tools primary tools Another signifi Another significant technological advancement has been cant technological advancement has been the onset of deep learning neural networks, in which the onset of deep learning neural networks, in which different layers of a multilayer network extract different different layers of a multilayer network extract different features until it can identify what exactly it is looking for. features until it can identify what exactly it is looking for. Basically, there are 3 parts that make up Basically, there are 3 parts that make up the architecture of a basic neural network. These include: of a basic neural network. These include: the architecture • Units/Neurons • Units/Neurons • Connections / Weights/ Parameters • Connections / Weights/ Parameters

3. • Biases • Biases All the above mentioned things are essential to construct All the above mentioned things are essential to construct the bare bones architecture of Neural Network. the bare bones architecture of Neural Network. What happens when a What happens when a Neural Net Neural Network Learns? work Learns? The most common way to teach neural network to The most common way to teach neural network to generalize to a problem is to use the Gradient Descent. generalize to a problem is to use the Gradient Descent. Coupled with GD, another way to teach neural network is Coupled with GD, another way to teach neural network is to use Back Propagation. Using this, the error at the to use Back Propagation. Using this, the error at the output layer of the neural net output layer of the neural network is propagated backwards using the chain backwards using the chain- -rule from calculus. This, however, can be very challenging for a beginner to however, can be very challenging for a beginner to understand without having a good command on calculus. work is propagated rule from calculus. This, understand without having a good command on calculus. Types of Neural Types of Neural Networks Networks There are many types of neural network; each one comes There are many types of neural network; each one comes with their own specific use cases and levels of complexity. with their own specific use cases and levels of complexity. The most basic type of neural net is something called a The most basic type of neural net is something called a feed forward neural network, in which the information feed forward neural network, in which the information travels in only one direction from input to output. travels in only one direction from input to output. One of the most widely used networ One of the most widely used networks is the recurrent neural network, in which data can flow in multiple neural network, in which data can flow in multiple directions. These neural networks come with greater directions. These neural networks come with greater learning abilities and are widely used for more complex learning abilities and are widely used for more complex tasks like learning handwriting. tasks like learning handwriting. ks is the recurrent

4. Apart from the above, there are also convolu Apart from the above, there are also convolution neural networks, Boltzmann machine networks, Hopfield networks, Boltzmann machine networks, Hopfield networks, and several others. Picking the right network networks, and several others. Picking the right network for your task completely depends on the data you have to for your task completely depends on the data you have to train it with, and the specific application you are thinking train it with, and the specific application you are thinking about in your mind. about in your mind. tion neural