What is an N-gram?

An n-gram is a connected sequence of n items in a given text or speech. Precisely, an N-gram is a probabilistic language model used to predict the next item in a particular sequence, as in (n-1). In the context of data analytics, an N-gram refers to a contiguous sequence of N items from a given … Read more

Name the statistical methods that are highly beneficial for data analysts?

The statistical methods that are mostly used by data analysts are: Bayesian method Markov process Simplex algorithm Imputation Spatial and cluster processes Rank statistics, percentile, outliers detection Mathematical optimization There are several statistical methods that are highly beneficial for data analysts. Here are some commonly used ones: Descriptive Statistics: Descriptive statistics summarize the main features … Read more

Define “Collaborative Filtering”

Collaborative filtering is an algorithm that creates a recommendation system based on the behavioral data of a user. For instance, online shopping sites usually compile a list of items under “recommended for you” based on your browsing history and previous purchases. The crucial components of this algorithm include users, objects, and their interest. In the … Read more

What is K-mean Algorithm?

K-mean is a partitioning technique in which objects are categorized into K groups. In this algorithm, the clusters are spherical with the data points are aligned around that cluster, and the variance of the clusters is similar to one another. The K-means algorithm is a popular unsupervised machine learning algorithm used for clustering data points … Read more

What is “Clustering?” Name the properties of clustering algorithms

Clustering is a method in which data is classified into clusters and groups. A clustering algorithm has the following properties: Hierarchical or flat Hard and soft Iterative Disjunctive Clustering is a technique used in data analytics and machine learning to group similar data points together based on certain features or characteristics. The goal of clustering … Read more