Handy Sheet Before your Next Interview — In this blog post, I’ve compiled a list of the top 25 most frequently asked questions about machine learning in interviews, along with comprehensive answers to help you ace your next interview. 1. What is Machine Learning? Machine learning is a subset of artificial intelligence that involves the use of algorithms to enable computers to…

Introduction Hypothesis testing is a critical statistical tool used in data science to draw conclusions and make informed decisions based on sample data. It is a systematic way of evaluating whether there is enough evidence to support or reject a particular claim or hypothesis about a population parameter. In hypothesis testing…

Introduction Selection bias in data science refers to the systematic error introduced in the sampling process, where the selection of data points is not random and does not represent the entire population. …

Introduction It refers to a situation where the combined analysis of data produces a different result or trend than what is observed when the data is analyzed in separate subsets or groups. This paradox can be deceptive, leading to incorrect interpretations and conclusions if not identified and addressed appropriately. In the…

Introduction In data science, understanding the different types of data is crucial in order to choose the appropriate analysis methods and draw valid conclusions from the data. There are four main types of data: nominal, ordinal, continuous, and discrete. Each type of data has its own properties and methods of analysis…

Standard Deviation Standard deviation is a statistical measure of how spread out a set of data is from its mean or average value. It is a measure of the amount of variation or dispersion of a set of data points. In machine learning: standard deviation is commonly used as a measure of…

Introduction In any data analysis project, it’s important to have a good understanding of the central tendency of the data. Central tendency refers to the typical or central value around which the data is distributed. There are three common measures of central tendency: mean, median, and mode. Each of these measures…

Basic Terminologies and Applications Intro Support Vector Machines (SVMs) are one of the most popular and widely used algorithms in the field of machine learning. They are particularly well-suited for classification problems, where the goal is to predict the class label of a new instance based on its features. In this…

Introduction In this post, I will be discussing the common issues and mistakes that can arise when working with machine learning. …