Interview Questions
📄 410 ArticlesMulticollinearity in Simple Terms
We all know the definition of multi-collinearity i.e. when 2 or more explanatory variable in multi regression model are highly […]
GRE Verbal | Barron’s 800 Destroyed | Day 10
We are already good with 220 words, lets’s pass that 250 mark. All the words given below are directly from […]
5 Most Important SQL questions for your Data Science Interview
SQL is the bread and butter of an analyst. You can’t survive in the Data Science industry with a grip […]
Cross Validation and varImp in R
I was onto our next book – Linear,Ridge, LAASO, and Elastic Net Algorithm explained in layman terms with code in […]
Ridge vs LASSO vs Elastic Net Regression
Ridge and LASSO are two important regression models which comes handy when Linear Regression fails to work. This topic needed […]
Linear, LASSO, Elastic Net, and Ridge Regression in Layman terms (R) with complete code – Part 1
Linear, LASSO, Elastic Net, and Ridge Regression are the four regression techniques which are helpful to predict or extrapolate the […]
One Hot Encoding – Feature Engineering
So, I just started solving the latest Hackathon on Analytics Vidhya, Women in the loop . Be it a real-life […]
Feature Engineering in Data Science
Have you ever wondered why two different people gets different accuracy while using the same algorithm?We all know that XGBoost […]
Correlation and Collinearity explained in layman terms
Correlation tells you have two numerical variables relate to each other. It will tell you whether data points that have […]
What is the difference between forecasting and prediction?
Forecasting and Prediction are two different things. You always forecast weather, but never predict the weather. Forecasting is nothing but […]