Among the myriad of machine learning algorithms and techniques available with data scientists, one stands out for its exceptional performance…
What is data science? This is a question that many people who are planning to start learning data science are…
Last updated: 25th Nov, 2023 Bagging is a type of an ensemble machine learning approach that combines the outputs from…
Last updated: 24th Nov, 2023 The activation functions are critical to understanding neural networks. There are many activation functions available…
Last updated: 24th Nov, 2023 Dimensionality reduction is an important technique in data analysis and machine learning that allows us…
There are two measures of the strength of linear regression models: adjusted r-squared and r-squared. While they are both important,…
While training machine learning models, we come across the need for scaling features in order to have different features contribute…
Last updated: 18th Nov, 2023 Machine learning (ML) models are increasingly being used to learn from data and make decisions…
Last updated: 18th Nov, 2023 Dimensionality reduction is an important technique in data analysis and machine learning that allows us…
The confusion matrix is an essential tool in the field of machine learning and statistics for evaluating the performance of…
Maximum Likelihood Estimation (MLE) is a fundamental statistical method for estimating the parameters of a statistical model that make the…
In linear regression, R-squared (R2) is a measure of how close the data points are to the fitted line. It…
Hierarchical clustering a type of unsupervised machine learning algorithm that stands out for its unique approach to grouping data points.…
Learning the concepts of Minimum Description Length (MDL) is valuable for several reasons, especially for those involved in statistics, machine…
Are you grappling with the complexities of choosing the right regression model for your data? You are not alone. When…
Have you ever encountered unfamiliar words while learning a new language and didn't know their meanings? Or tried to fit…