## The Workflow of Neural Network: Forward Propagation and Backpropagation

The Neural Network has been developed to mimic a human brain. Though we are not there yet, neural networks are very efficient in machine learning. It was very popular in…

The Neural Network has been developed to mimic a human brain. Though we are not there yet, neural networks are very efficient in machine learning. It was very popular in…

Logistic regression is a popular method since the last century. It establishes the relationship between a categorical variable and one or more independent variables. This relationship is used in machine…

Logistic regression is a powerful classification tool. It can be applied only if the dependent variable is categorical. There are a few different ways to implement it. Today I will…

Polynomial regression in an improved version of linear regression. If you know linear regression, it will be simple for you. If not, I will explain the formulas here in this…

In this article, learn how to develop an algorithm using Python for multiclass classification with logistic regression one vs all method described in week 4 of Andrew Ng’s machine learning…

Recurrent Neural Network (RNN) Say, you live in an apartment where you got lucky enough to get a roommate who makes dinner every night. He makes either of these three…

Neural networks are pretty old algorithms for machine learning, developed originally with the idea to mimic human brain. For sure, human brain has the best learning mechanisms we know. If…

Logistic regression is one of the most widely used classification algorithms. In one of my previous blogs, I talked about the definition, use and types of logistic regression. In this…

The term logistic regression can be deceptive. Because Actually it is classification model. We use logistic regression to solve problems like: Emails are spam or not. Online transactions are: fraudulent…

Gradient descent is a very important parameter in machine learning. Gradient descent is used to minimize different functions. In machine learning it is used to update important parameters. The goal…