Perceptron Learning Algorithm SONAR Data Classification Edureka

As you know a perceptron serves as a basic building block for creating a deep neural network therefore, it is quite obvious that we should begin our journey of mastering Deep Learning with perceptron and learn how to implement it using TensorFlow to solve different problems. In case you are completely new to deep learning, I would suggest you to go through the previous blog of this Deep Learning Tutorial series to avoid any confusion. Basically, a problem is said to be linearly separable if you can classify the data set into two categories or classes using a single line. On the contrary, in case of a non-linearly separable problems, the data set contains multiple classes and requires non-linear line for separating them into their respective classes. Let us visualize the difference between the two by plotting the graph of a linearly separable problem and non-linearly problem data set:Since, you all are familiar with AND Gates, I will be using it as an example to explain how a perceptron works as a linear classifier.