Feature engineering is the process of using domain knowledge to extract features from raw data via data mining techniques. These features can be used to improve the performance of machine learning algorithms. Feature engineering is most important step for any data scientist.

What is a Variable?

A variable is any…


One Hot Encoding

One hot encoding, consists in encoding each categorical variable with different boolean variables (also called dummy variables) which take values 0 or 1, indicating if a category is present in an observation.

For example, for the categorical variable “Gender”, with labels ‘female’ and ‘male’, we can generate…


“Artificial Neural Network” is derived from biological neural networks that develop the structure of a human brain. Like the human brain, ANN also have neurons that are interconnected to one another in various layers of the networks. These neurons are known as nodes.

The architecture of an artificial neural network

Input Layer

As the name suggests, it…


Feature Scaling

Feature scaling refers to the methods or techniques used to normalize the range of independent variables in our data, or in other words, the methods to set the feature value range within a similar scale. …


Label / integers encoding: definition

  • Integer encoding consist in replacing the categories by digits from 1 to n (or 0 to n-1, depending the implementation), where n is the number of distinct categories of the variable.
  • • The numbers are assigned arbitrarily.

• This encoding method allows for quick benchmarking…

Ankush kunwar

Data science enthusiastic

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