Machine learning models are often trained with a variety of different methods in order to create a more accurate prediction.…
The Classification and Regression Tree (CART) is a supervised machine learning algorithm used for classification, regression. In this blog, we…
Decision tree is one of the most commonly used machine learning algorithms which can be used for solving both classification…
The two-way analysis of variance (ANOVA) test is a powerful tool for analyzing data and uncovering relationships between a dependent…
In statistics, population and sample are two fundamental concepts that help us to better understand data. A population is a…
Bayesian thinking is a powerful way of looking at the world, and it can be useful in many real-life situations.…
Understanding the differences between true error and sample error is an important aspect of data science. In this blog post,…
In this post, you will learn about the statistics concepts of confidence intervals in relation to machine learning models with…
Hidden Markov models (HMMs) are a type of statistical modeling that has been used for several years. They have been…
The Levene test is used to test for equality of variance in a dataset. It is used in statistical analysis…
Everyone knows that data visualization is one of the most important tools for any data scientist or statistician. It helps…
In this post, you will learn the definition of 25 different types of probability distributions. Probability distributions play an important…
In data science, variables are the building blocks of any analysis. They allow us to group, compare, and contrast data…
Machine learning is a field of artificial intelligence that deals with giving machines the ability to learn without being explicitly…
Clustering is a type of unsupervised machine learning technique that is used to group data points into distinct categories or…
Have you ever heard of the term "Python Pickle"? If not, don't feel bad—it can be a confusing concept. However,…