Post by Author : somto_achu

In machine learning, optimizing the learning models is a critical step. This is where Gradient Descent emerges as a central optimizing algorithm. What is Gradient Descent? Machine learning hinges on creating models that predict outcomes from various inputs. However, these models don’t start perfectly; they initially operate on random parameters, which are not ideal for making accurate predictions. Creating a

Logistic Regression and Linear Regression are two fundamental statistical methods used for predictive modeling within the supervised machine learning framework. Before discussing these two concepts, let’s discuss what regression is and the use of regression analysis in machine learning. What is Regression Regression in statistics refers to a type of predictive modeling technique that analyzes the relationship between a dependent

Activation functions are mathematical equations attached to the end of every layer of an artificial (deep) neural network. This helps in computing the output and figuring out if nodes would fire or not. They also help neutral networks learn complex nonlinear relationships in data. What Does Node’s Firing Mean The phrase “node will fire or not” is a metaphorical way

This article will discuss building a simple neural network using JavaScript. However, let’s first check what deep neural networks and artificial neural networks are. Deep Neural Network and Artificial Neural Network Artificial Neural Networks (ANNs) and Deep Neural Networks (DNNs) are related concepts, but they are different. The inspiration behind these artificial neural networks for machine learning and artificial intelligence