2022-06-23

A tutorial on Pandas apply, applymap, map, and transform

16 mins read In Data Processing, it is often necessary to perform operations (such as statistical calculations, splitting, or substituting values) on a […]
2022-06-19

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 […]
2022-06-19

Understanding Micro, Macro, and Weighted Averages for Scikit-Learn metrics in multi-class classification with example

11 mins read The F1 score (aka F-measure) is a popular metric for evaluating the performance of a classification model. In the case […]
2022-06-19

Why are precision, recall, and F1 score equal when using micro averaging in a multi-class problem?

9 mins read In one of my projects, I was wondering why I get the exact same value for precision, recall, and the F1 score when using scikit-learn’s metrics. […]
2022-06-18

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 […]
2022-06-15

Understanding Contiguous vs Non-Contiguous Tensors in PyTorch

13 mins read Tensor and View View uses the same data chunk from the original tensor, just a different way to ‘view’ its […]
2022-06-14

Deploying and sharing Machine Learning projects easily using Gradio

7 mins read Students or Professionals from other streams, like business studies, practice and excel in data science. But when it comes to […]
2022-06-03

A complete guide on feature selection techniques with Python code

33 mins read Considering you are working on high-dimensional data that’s coming from IoT sensors or healthcare with hundreds to thousands of features, […]
2022-05-30

A tutorial on Scikit-Learn Pipeline, ColumnTransformer, and FeatureUnion

20 mins read These three powerful tools are must-know for anyone who wants to master using sklearn. It’s, therefore, crucial to learn how to […]
2022-05-29

Understanding different types of Scikit Learn Cross Validation methods

14 mins read Cross-validation is an important concept in machine learning which helps the data scientists in two major ways: it can reduce the […]
2022-05-28

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 […]
2022-05-28

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 […]
2022-05-26

Understanding Ordinal and One-Hot Encodings for categorical features

21 mins read Machine learning models require all input and output variables to be numeric. This means that if your data contains categorical […]
2022-05-26

When should we drop the first one-hot encoded column?

10 mins read Many machine learning models demand that categorical features are converted to a format they can comprehend via a widely used […]
2022-05-26

Alternatives for One-Hot Encoding of Categorical Variables

6 mins read One-hot encoding, otherwise known as dummy variables, is a method of converting categorical variables into several binary columns, where a […]