Megha Verma

Jun
21
Supervised Learning and its different types

Supervised Learning and its different types

Supervised learning, is a subcategory of machine learning and artificial intelligence. It is defined by its use of labeled datasets to train algorithms that to classify data or predict outcomes accurately.
2 min read
Jun
21
Unsupervised Learning

Unsupervised Learning

Unsupervised learning is a type of machine learning in which models are trained using unlabeled dataset and are allowed to act on that data without any supervision
1 min read
Jun
21
Understanding Bayes' Theorem

Understanding Bayes' Theorem

Bayes’ Theorem is perhaps the most important theorem in the field of mathematical statistics and probability theory. For this reason, the theorem finds its use very often in the field of data science.
2 min read
Jun
11
Data Mining- An Overview

Data Mining- An Overview

Data mining is an interdisciplinary subfield of computer science and statistics with an overall goal to extract information from a data set and transform the information into a comprehensible structure for further use.
2 min read
Jun
11
Introduction to Classification in Machine Learning

Introduction to Classification in Machine Learning

Classification is a process of categorizing a given set of data into classes, It can be performed on both structured or unstructured data.
2 min read
Jun
08
Introduction to Dimensionality Reduction

Introduction to Dimensionality Reduction

Dimensionality reduction is the process of reducing the number of random variables under consideration, by obtaining a set of principal variables.
2 min read
Jun
08
Clustering Vs Classification

Clustering Vs Classification

Clustering is an unsupervised machine learning method of identifying and grouping similar data points in larger datasets without concern for the specific outcome whereas classification refers to a predictive modeling problem where a class label is predicted for a given example of input data.
2 min read
May
31
Hypothesis Testing in Data Science

Hypothesis Testing in Data Science

Hypothesis Testing is necessary for almost every sector, it does not limit to Statisticians or Data Scientists. For example, if we develop a code we perform testing too. In the same way, for every product or problem that an organization shows, it has to be solved by providing assumptions.
3 min read
May
31
Introduction to K-Means Clustering

Introduction to K-Means Clustering

K-means clustering is one of the most common unsupervised learning algorithms in Data Science.
2 min read
May
31
Introduction to Decision Tree Algorithm

Introduction to Decision Tree Algorithm

In its simplest form, a decision tree is a type of flowchart that shows a clear pathway to a decision. In terms of data analytics, it is a type of algorithm that includes conditional ‘control’ statements to classify data.
3 min read