Evaluation metrics for Multi-Label Classification with Python codes

10 mins read In a traditional classification problem formulation, classes are mutually exclusive. In other words, under the condition of mutual exclusivity, each […]

A guide on regression error metrics (MSE, RMSE, MAE, MAPE, sMAPE, MPE) with Python code

25 mins read Regressions are one of the most commonly used tools in a data scientist’s kit. The quality of a regression model is how […]

How to interpret logistic regression coefficients?

15 mins read Logistic Regression is a fairly simple yet powerful Machine Learning model that can be applied to various use cases. It’s […]

Understanding interaction effects in regression analysis

22 mins read In regression, an interaction effect exists when the effect of an independent variable on a dependent variable changes, depending on […]

Performing A/B test in Python example – A case study from Udacity Data Scientist Nano Degree

11 mins read This is a simple walkthrough of an A/B test case study developed and used by Udacity. It is part of […]

A guide to Bootstrapping for Statistical Inference – Confidence Interval and Hypothesis Testing

14 mins read Introduction Inferential Statistics is the process of examining the observed data (sample) in order to make conclusions about the properties/parameters […]

Understanding p-value using bootstrapping technique in statistics

13 mins read For context, we are using the bootstrapping methods (that I’ve referenced previously) for simulating null and sampling distributions (rather than standard […]

Understanding Bootstrapping approach vs. Traditional approaches in statistics

13 mins read Bootstrapping is a statistical procedure that resamples a single dataset to create many simulated samples. This process allows you to […]

Understanding Jacobian and Hessian matrices with example

19 mins read In this post, you will find what the Jacobian matrix and the Hessian matrix are and how to calculate them. […]

Understanding and interpreting Residuals Plot for linear regression

27 mins read Interpreting Residual Plots to Improve Your Regression When you run a regression, calculating and plotting residuals help you understand and improve your […]

Understanding Discrete Fourier Transformation with mathematics and Python codes

16 mins read Introduction The Fourier Transformation is applied in engineering to determine the dominant frequencies in a vibration signal. When the dominant […]

Mathematical view of Bias-Variance trade-off

6 mins read The bias-variance trade-off is an important concept in statistics and machine learning. This is used to get better performance out […]

Understanding Gaussian Process

79 mins read Gaussian Process is a machine learning technique. You can use it to do regression, classification, among many other things. Being […]

Steps to sample from a multivariate Gaussian (Normal) distribution with Python code

2 mins read Steps: A widely used method for drawing (sampling) a random vector x from the N-dimensional multivariate normal distribution with mean vector μ and covariance matrix Σ works as […]

Solving six problems with Bayesian statistics

8 mins read 1) The first one is a warm-up problem. Suppose there are two full bowls of cookies. Bowl #1 has 10 […]