The latest technological advancements in Data Sciences and Machine Learning have helped transform the way we live and interact with our surroundings. We are constantly generating exponential amounts of data at a very fast pace, which the big tech companies ...

Classification and regression trees (CART) may be a term used to describe decision tree algorithms that are used for classification and regression learning tasks. CART was introduced in the year 1984 by Leo Breiman, Jerome Friedman, Richard Olshen and Charles ...

When we have a large number of data and we want to take insights out of them then the main step we want to do is to visualise that data. It explains how our data is behaving under a certain ...

AdaBoost is a short form for “Adaptive Boosting” which is the first practical boosting algorithm proposed by Freund and Schapire in 1996. It focuses on classification problems and aims to convert a group of weak classifiers into a robust one. The ...

The use of randomness is an important part of the configuration and evaluation in Python and its application. In this article, we will discover how to generate and work with random numbers in Python. Especially machine learning algorithms (Python is ...

Chess is a strategy game played by two players on a board which is very popular worldwide. It has 64 squares arranged in an 8×8 square grid with the concept of winning the space by two kings with his whole ...

Clustering or cluster analysis is an unsupervised learning problem. It is often used as a knowledge analysis technique for locating interesting patterns in data, like groups of consumers supported their behaviour. There are many clustering algorithms to settle on from ...

Math helps in understanding logical reasoning and attention to detail. It enhances your abilities to think under pressure and increase your mental endurance. Mathematical concepts give the real solution of hypothetical or virtual problems. It is about structure, developing principles ...

Chicken and egg problems are major headaches for several entrepreneurs. Many machine learning (ML) problems affect an identical dilemma. If we all know A, we will determine B. Or, if we all know B, we will determine A. Either way ...

Stacking is an ensemble machine learning technique that allows combining different prediction models to make a single model that make the final prediction out of the provided dataset. Sometimes these combined models can be same depending up to the type ...