Understanding Artificial Neural Network With Linear Regression | Developers Corner - Analytics India Magazine

Artificial Neural Network (ANN) is probably the first stop for anyone who enters into the field of Deep Learning, continues Analytics India Magazine.

Photo: Analytics India Magazine

Inspired by the structure of Natural Neural Network present in our body, ANN mimics a similar structure and learning mechanism.

ANN is just an algorithm to build an efficient predictive model. Because the algorithm and so its implementation resembles a typical neural network, it is named so. The functionality of ANN can be explained in below 5 simple steps:

1. Read the input data
2. Produce the predictive model (A mathematical function)
3. Measure the error in the predictive model
4. Inform and implement necessary corrections to the model repeatedly until a model with least error is found
5. Use this model for predicting the unknown

A beginner in data science, after going through the concepts of Regression, Classification, Feature Engineering etc. and enters into the field of deep learning, it would be very beneficial if one can relate the functionality of algorithms in deep learning with above concepts...

Everyone agrees that simple linear regression is the simplest thing in machine learning or atleast the first thing that anyone learns in machine learning. So, we will try to understand this concept of deep learning also with a simple linear regression, by solving a regression problem using ANN.
Read more...

Source: Analytics India Magazine