Data Science Articles

Alyssa Schroer

Updated on April 18, 2025

These companies use AI to enhance business processes, from automating customer support to beefing up cybersecurity.

Margo Steines

Updated on April 18, 2025

Data science jobs at these companies require knowledge of relevant tools and programming languages.

Erdem İŞBİLEN

Updated on April 18, 2025

The law of large numbers states that increasing the number of trials leads the average of the results to approach an expected value more closely. Here’s how the law works, why it matters, its types and examples of how it’s used.

Nikola Ilic

Updated on April 18, 2025

Dynamic filtering allows Power BI users to customize how data is displayed and interact with the data without using bookmarks or buttons. Follow these steps to create a dynamic filter in Power BI.

Sunny Srinidhi

Updated on April 18, 2025

Lemmatization is a text pre-processing technique used in natural language processing (NLP) models to break a word down to its root meaning to identify similarities. It is one of the most common text pre-processing techniques used in NLP.

Abhijeet Pujara

Updated on April 18, 2025

MobileNet is a mobile-first class of convolutional neural network (CNN) that was open-sourced by Google and provides a starting point for training classifiers through a lightweight model.

Catherine Gitau

Updated on April 17, 2025

Fuzzy string matching is the process of finding strings that approximately match each other. Here’s more on how fuzzy string matching works and how to perform the process using the Python library FuzzyWuzzy.

Abdishakur Hassan

Updated on April 17, 2025

Extrapolation is a statistical technique that uses existing data to predict future or unknown values that fall outside the range of the existing data. Here are common extrapolation methods, how extrapolation works and its pros and cons.

Edoardo Romani

Updated on April 17, 2025

Database normalization refers to organizing data into tables to improve the efficiency of a database and ensure the consistency and accuracy of its data. Here’s why it matters and the normal forms involved in the process.

Peter Grant

Updated on April 17, 2025

Model validation is a phase in the machine learning process where a trained model’s performance is evaluated using data that is different from the training data, known as a validation data set.