Learn the Adagrad optimization algorithm, how it works, and how to implement it from scratch in Python for machine learning models. #Adagrad #Optimization #Python Why presidents stumble in this most ...

The goal of a machine learning regression problem is to predict a single numeric value. There are roughly a dozen different regression techniques such as basic linear regression, k-nearest neighbors ...

1 PG & Research Department of Computer Science, D.G.Vaishnav College, Chennai, India. 2 PG Department of IT & BCA, D.G.Vaishnav College, Chennai, India. 3 Department of Computer Science, Souht East ...

The use of machine learning algorithms to identify characteristics in Distributed Denial of Service (DDoS) attacks has emerged as a powerful approach in cybersecurity. DDoS attacks, which aim to ...

Naive Bayes is a probabilistic machine learning algorithm that can be used to solve a wide range of classification problems. Typical applications include spam filtering, document classification, ...

GREP is a command-line utility for searching plain-text data sets for lines that match a regular expression or simply a string. In this, I implemented GREP using Naive Search.

Abstract: In this paper, we propose an implementation of Naïve Bayes algorithm in a chase game called Maze Chase. Maze Chase is a chase game where a player must avoid several chasings Non-Player ...

Abstract: The growth of internet usage increased the need of security in network which is monitored by Intrusion Detection System (IDS). Using machine learning algorithms is common for implementing ...