A Quick Guide To Make Your Own Neural Network Using Python
As part of a quest to learn more and more about Artificial Intelligence or AI, several enthusiastic IT students set themselves the goal of building a simple and effective neural network for explicitly understanding the Neural Machine Learning methods and progress in the field.
But is it that simple to Make Your Own Neural Network?
Of course ‘Yes,’ only when you know where to learn the tricks! Here’re few tips and tricks which will help you create your own AI Neutral Network! But Before that; let’s check out what Neutral Network is!
Neural networks are a system of Artificial Intelligence (AI) which process information in an identical manner the human brain does. The interface is primarily made of up a verity of highly interrelated processing elements or neurons; working conjointly to solve a specific problem.
Tips To Create Neutral Network
For any aspiring Data Scientists, understanding the inner essentials and workings of a Neural Network is vital to develop a Neutral Network in the domain of Artificial Intelligence. Basically, Neural Networks are made up of some crucial components including:
ü An input layer, x
ü A random amount of hidden layers
ü An output layer, ŷ
ü A chain of weights and biases between every layer, W and b
ü Also an option of activation function for every hidden layer, σ
ü Steps To Build Neutral Network
ü Start with setting each weight to an arbitrary number
ü Adjust Weights using the “Error Weighted Derivative” formula
ü Now Construct the Python code using Python mathematics library known as Numpy
That’s it! Now, Try running the neural network using the Terminal command, created by you!