The basic building block of neural networks is

• Neuron

• Perceptron

Perceptron is a mathematical model mimics

• human brain

• human neuron

Pandas library used to deal with

• Graphical representation of data.

• Datasets reshaping and pivoting

• Numerical Python is linear algebra and matrix calculations produced in Python.

• Machine learning Functions

• graphical representation of data.

Numpy library used to deal with

• Graphical representation of data.

• Datasets reshaping and pivoting

• Numerical Python is linear algebra and matrix calculations produced in Python.

• Machine learning Functions

• graphical representation of data.

Matplotlib library used to deal with

• Graphical representation of data.

• Datasets reshaping and pivoting

• Numerical Python is linear algebra and matrix calculations produced in Python.

• Machine learning Functions

• graphical representation of data.

Scikit-Learn library used to deal with

• Graphical representation of data.

• Datasets reshaping and pivoting

• Numerical Python is linear algebra and matrix calculations produced in Python.

• Machine learning Functions

• graphical representation of data.

perceptron ---------is either an external trigger from the environment or comes from outputs of other artificial neurons

• input

• weight

• net input function

• activation function

• output

perceptron ---------factors that are multiplied by the entries which correspond to them, increasing or decreasing their value

• input

• weight

• net input function

• activation function

• output

perceptron ---------the summation of weights multiplied by inputs or stimulate from others

• input

• weight

• net input function

• activation function

• output

perceptron ---------It decides whether or not a neuron should be activated.

• input

• weight

• net input function

• activation function

• output