The ‘self’ is a keyword used in object-oriented programming to refer to the instance of a class. It acts as a placeholder for the instance itself, providing access to the attributes and methods defined within the class. When a method…
PyTorch is a popular Python library that helps all deep learning enthusiasts. The torch.nn module is a very important component of PyTorch which helps with the building and training of neural networks. In this article, we will take a deep…
Pytorch is a prevalent machine learning library in Python programming language. Pytorch is a handy tool in neural networks and torch.optim module is used in various neural network models for training. This module provides us with multiple optimization algorithms for…
Non-parametric statistics do not assume any strong assumptions of the distribution, which contrasts with parametric statistics. Non-parametric statistics focus on ranks and signs along with minimal assumptions. Non-parametric statistics focus on analyzing data without making strong assumptions about the underlying…
Maximum a posteriori ( MAP ) is an estimation technique that estimates the most probable value ( mode ) of an unknown quantity of some data. In this article, we calculate MAP using the combination of prior distribution and likelihood…
McNemar’s test is a statistical method used to compare paired categorical data with two categories, often used to evaluate the effectiveness of a treatment or intervention. It involves creating a 2×2 contingency table, calculating the test statistic, and comparing it…
Let’s start with a real-world example – Cars are mostly graded on the mileage they can handle. Good mileage cars are preferred due to rising fuel costs and hence it is a headache for car manufacturers as they have to…
All machine learning enthusiasts have a frustrating time with which parameters to use to make their models effective. Bad parameters or features can potentially ruin the model and can also have adverse consequences. So how do we tackle this problem?…
In today’s world, we get products recommended everywhere or anywhere we go. From Amazon to Flipkart to Myntra, we just keep on buying the best-rated products recommended to us. Have you ever wondered how this happens? All this is made…
Information entropy is the amount of uncertainty involved in predicting the outcome of an event. The higher the entropy, the more uncertain the outcome. This article explains the concept of information entropy, provides its mathematical representation, and demonstrates its calculation…