Decision trees are one of the most commonly used technique among all business analysts. It helps us with the prediction and...

The classification problem is a type of supervised problem in which the target variable is categorical in nature. In this article, we...

In unsupervised learning where we don't have a target variable, we try to find patterns based on their observation, features. Based on...

The main aim of any machine learning model is to perform well on unseen data. It is important that the model performs well on training as...

After model building using a different algorithm, we can evaluate the performance of the model using different evaluation metrics....

Dividing data set into train and test is one method to quickly evaluate the performance of the algorithm on the problem. The training...

After completing previous stages of predictive modeling, problem definition, hypothesis generation, data extraction, data exploration, we...

What is variable transformation? Variable transformation is a process by which we replace a variable with some function of that variable....

Reason for outliers An outlier is a data point that differs significantly from other observations. The outlier present in the data set...

Reasons for missing values in data. Missing values in data are due to many reasons. one of these is non-response, like when you collect...

Univariate Analysis What is a univariate analysis? What is the use of univariate analysis? univariate analysis is when we focus on a...

What is a data exploration Data exploration is the fourth stage of predictive modeling. This process helps to gain insights from data. A...

After problem definition, the next stage of predictive modeling is hypothesis generation. A hypothesis is an opinion or view of a problem...

Most of the organizations are heavily investing in advanced analytics and predictive modeling. This can be the motivation for why we have...

Predictive modeling is a process that uses past data and other attributes to predict outcomes with the data model. Now with this...

Welcome to this journey of machine learning life cycle in 15 days. Before starting this one should have a bit of programming experience...