In Deep Learning Artificial Neural Network is a comprehensive and mathematical way of explaining a simple 2-layered neural network by coding one from scratch in python and behind the scenes of such popular algorithms. First, we provided with a rationale view of the study behind the elaboration of these algorithms and mathematical intuition behind them. Then, we dived into the coding of neural network mixing python lines of code and mathematical equations. In this research, we created a two-layered neural network with a hidden layer to minimize time and effort resulting with more accurate and efficient output, but the idea remains the same for more than two-layered neural networks. Finally, we worked on how we could publicize our model and make it more adaptable for solving complex real-life issues and our experimental results showed that our 2-layered network model could achieve more accuracy and reliable measures as compared to other network methods for solving such complex problems.
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