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K-means clustering is a type of unsupervised learning when we have unlabeled data (i.e., data without defined categories or groups). Clustering refers to a collection of data points based on specific similarities. K-Means Algorithm K-means aims to find groups in the data, with the number of groups represented by the variable K. Based on the provided features, the algorithm works

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

When we cluster things, we put them into groups. In Machine Learning, Clustering is the process of dividing data points into particular groups. One group will have similar data points and differentiate from those with other data points. It is purely based on the patterns, relationships, and correlations in the data. Clustering is a form of Unsupervised Learning. Let’s quickly

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

In the ever-evolving landscape of technology, the pursuit of Artificial General Intelligence (AGI) stands as one of our time’s most ambitious and consequential endeavors. AGI aims to create machines with the ability to understand, learn, and apply intelligence as flexibly and robustly as a human. Therefore, it is not just a milestone in artificial intelligence; it is a potential turning

Machine Learning is making a buzz in the industry. And it’s the right time to get familiar with it. Let’s get the basics right. Let’s get started. What is Machine Learning What the heck is machine learning? If I had to quote it in a single sentence, I would say, ‘Machine Learning is a way to find a pattern in

Performance metrics are numbers that help measure the efficiency of your machine-learning algorithm and determine whether it’s solving the problem correctly. They also help compare and evaluate different algorithms for the same use case and determine which one you should go ahead with. The decision of which performance metric to use for your machine learning problem first depends on the

A Bayesian network is a graphical model representing probabilistic relationships among variables. This helps in understanding how different factors influence each other and in predicting the behavior of one variable based on the others. Purposes Served by Bayesian Network In machine learning, a Bayesian network serves several key purposes: These capabilities make Bayesian networks a powerful tool in areas such