## Multicollinearity

With increasingly advanced machine learning and deep learning algorithms, you can solve almost any problem with proper datasets. However, as the complexity of the...

Skip to content# Data Science Team

## Multicollinearity

## Chi Test

## Log Loss

## Singular value decomposition

## Relu Activation Function

## Confounding Variable

## Confusion Matrix

## Feature Engineering

## Power Analysis

## SMOTE

With increasingly advanced machine learning and deep learning algorithms, you can solve almost any problem with proper datasets. However, as the complexity of the...

When developing a machine learning model, you may encounter numerous problems. One common problem related to feature selection determines how relevant the input features...

In machine learning, you can solve predictive modeling through classification problems. For each observation in the model, you must predict the class label. The...

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

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...

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...

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

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

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

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

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