Customer churn, also known as customer attrition, is a major problem for businesses that rely on recurring revenue. Customer churn…
In this blog post, we will be going over a very simple example of how to train a stacking classifier…
In this blog post, we will tune the hyperparameters of a Decision Tree Classifier using Grid Search. In machine learning,…
In this blog post, we'll learn about some real-world / real-life examples of Reinforcement learning, one of the different approaches to…
The passive aggressive classifier is a machine learning algorithm that is used for classification tasks. This algorithm is a modification…
Generalized linear models (GLMs) are a powerful tool for data scientists, providing a flexible way to model data. In this…
Google Colab is a powerful tool that allows you to run Python code in the cloud. This can be useful…
In machine learning, ridge classification is a technique used to analyze linear discriminant models. It is a form of regularization…
Pandas is a library for data analysis in Python. It offers a wide range of features, including working with missing…
In this post, you will learning about concepts about machine learning (ML) pipeline and how to build ML pipeline using Python…
Time-series forecasting is a specific type of forecasting / predictive modeling that uses historical data to predict future trends in…
A lot of beginners in the field of data science / machine learning are intimidated by the prospect of doing…
Ranking algorithms are used to rank items in a dataset according to some criterion. Ranking algorithms can be divided into…
Knowledge graphs and machine learning are two important tools for understanding and making decisions in business. Knowledge graphs can be…
AI / Machine learning (ML) based solutions / applications have become increasingly important in business and industry. However, with the…
Targeted advertising is nothing new. Businesses have been using targeted ads for years in order to try and increase sales.…