nikhilamunipalli

cognitive_marketing_cloud

codeutsava3.0

Adobe-React-Aug-2020

gobingo

sentiment-analysis-with-deep-learning-and-GANs

GANs-ANNs-ensemble-classification

generative-adversarial-networks-GANs-

simple gans

restricted-boltzmann-machines-artificial-neural-networks-for-binary-classifiation

javascript_dicegame

keyword

nlp-for-religion-prediction

restricted-boltzmann-machines-for-classification

artificial-neural-networks-classification

anEngineer

regression-models

classification-models

sentiment

sentiment_analysis

android-projects

Categorical-data-handling

When your data involves many categorical variables, a simple logic can be used to encode them. After label encoding is done, OneHotEncoder is used to encode the already encoded data into 0s and 1s. Later one of the encoded column must be eliminated to remove Dummy Variable Trap. For this, several numpy vectors must be created which can store individual categorically encoded variable. Instead of usage of many arrays and later appending them to independent variable matrix, every variable can be encoded at a time and dummy variable trap can be eliminated. This is a simple loop implementation, using enumeration technique.

github-demo

a simple demo repository to show the Git Workflow

hello-world

this is my first github project