Key statistical concepts for your data science or data analysis journey — As Karl Pearson, a British mathematician has once stated, Statistics is the grammar of science and this holds especially for Computer and Information Sciences, Physical Science, and Biological Science. When you are getting started with your journey in Data Science or Data Analytics, having statistical knowledge will help you to…

A ready-to-run code with different data sampling techniques to create a random and representative sample in Python — Data Sampling forms the essential part of the majority of research, scientific and data experiments. It is one of the most important factors which determines the accuracy of your research or survey result. If your sample has not been accurately sampled then this might impact significantly the final results and…

Your Guide to Monte Carlo Simulation and Must Know Statistical Sampling Techniques With Python Implementation — Monte Carlo Simulation is based on repeated random sampling. The underlying concept of Monte Carlo is to use randomness to solve problems that might be deterministic in principle. Monte Carlo simulation is one of the most popular techniques to draw inferences about a population without knowing the true underlying population…

Everything you need to know about the simplest yet the most popular Machine Learning regression model — Correlation is not causation. — Kenneth L. Woodward The first thing you can read in every statistics book is that correlation is not causation. However, it’s also the first thing many students forget once they see their data and start to look for insights about it. Linear Regression is one…

Must know statistical tests for testing statistical significance of features in Regression Model: One-sided & Two-sided T-test, F-test — “Facts are stubborn things, but statistics are pliable.” ― Mark Twain Trying to determine whether a variable or set of variables had a real impact on another, dependent, variable is one of the most common reasons for using regression models such as Linear Regression.

End-to-end Data Science Case Study to Crack Spotify Onsite Interview with Tips and Python Implementation — If you are preparing for your Data Science or Data Consultant Case Study interview then this article is for you. This end-to-end Data Science Case Study with its Python implementation, asked during the final stage of recruitment processes will help you to get an understanding where to start and what…

Movie list to get inspired, motivated, and expand your horizons — This is a movie list, in no particular order, that in my humble opinion everyone must watch. These are certainly not all but most of my favorite movies some of which got me inspired, motivated, or taught me a thing or two. These movies will leave you speechless and they…

List of exact Python/SQL commands and experimentation topics you should know to nail Spotify Tech Screen — If you are preparing for Technical Screen or Technical Interview at Spotify then most likely you are looking for answers to the following questions: How can I start preparing for Spotify Data Science tech interview? What can I expect from Spotify Data Science tech interview? This article will cover the…

Introduction to bias-variance trade-off, overfitting & how to solve overfitting using regularization: Ridge and Lasso Regressions — “It is better to be approximately right than precisely wrong” ― Warren Buffett Overfitting is an important issue that forms the essential part of every Data Scientist’s and Machine Learning Engineer’s modeling checklist. So, if you are using a Statistical, Econometrical or Machine Learning model, no matter how simple your…