Data Science Team, Author at DATA SCIENCE

Singular value decomposition

Principal component analysis and singular value decomposition are among the two common concepts of linear algebra in machine learning. After collecting raw data, is...

Machine Learning

Relu Activation Function

Activate function is an essential element for designing a neural network. Choosing the activation function will give you complete control over the network model’s...

Machine Learning

Confounding Variable

Confounding variable is a statistical term.The concept is a bit confusing for many people because of the method to use. For starters, different researchers...

Machine Learning

Confusion Matrix

The classification process helps with the categorization of the dataset into different classes. A machine learning model enables you to: Frame the problem, Collect...

Machine Learning

Feature Engineering

Every machine learning algorithm analyzes and processes input data and generates the outputs. The input data includes features in columns. These columns are structured...

Machine Learning

Power Analysis

A hypothesis test for statistical power will help detect the probability of an effect. You can only spot the true effect if available. With...

Computer programming

SMOTE

This article will discuss how SMOTE module helps increase underrepresented numbers in the dataset of a machine learning model. SMOTE is the best method...

Mathematics & statistics

Box Plot Review

A box plot or box and whisker plot help you display the database distribution on a five-number summary. The first quartile Q1 will be...

Machine Learning

Generative Adversarial Networks

In this article, you will learn about generative adversarial networks or GANs. Generative adversarial networks are the generative modeling approach for deep learning techniques....

Machine Learning

Transfer Learning

As the datasets increase drastically, we are developing skills to enhance the way we train deep neural networks. This helps data scientists map the...