Gradient descent is an optimization algorithm used in machine learning and deep learning to minimize a function, essentially finding the best model parameters that minimize the error on the data. The basic idea of gradient descent is to find the direction of the steepest slope …
Graphics Processing Units (GPUs) have come a long way since their inception as dedicated hardware for rendering graphics in video games. As computer scientists and engineers began to recognize their potential beyond gaming, GPUs have become an essential component in numerous fields, including artificial intelligence, …
What is Machine Learning? Machine learning (ML) is a subset of artificial intelligence that focuses on enabling machines to learn from and make decisions based on data, without being explicitly programmed. In other words, ML algorithms allow computers to ‘learn’ from data and improve their …
The world of machine learning can be daunting, especially for beginners. However, some techniques are much easier to understand than others. One such technique is the Naive Bayes Classifier. This article will break down the concept in layman’s terms so that you can grasp the …
Machine learning can seem like a daunting field, especially when you’re faced with complex terms and techniques. Fear not! In this article, we’ll break down regularization methods, specifically LASSO, Ridge, and similar techniques, into simple, easy-to-understand terms so that even beginners can grasp the basics. …
Principal Component Analysis (PCA) might sound like an intimidating concept, but it’s actually a simple and powerful technique widely used in the world of data analysis. In this article, we’ll break down PCA in a way that’s easy to understand, even if you’re a complete …
Welcome to the world of exploratory data analysis (EDA)! If you’re new to the field of data science or simply looking to brush up on your understanding of EDA, you’ve come to the right place. This article aims to provide an easy-to-follow, beginner-friendly guide to …
Models are an integral part of our daily lives, even if we may not always be consciously aware of them. They are representations of real-world systems that help us understand, analyze, and predict various phenomena. In the context of machine learning and data science, modeling …
Machine learning, a subfield of artificial intelligence, has been transforming industries and improving our lives through innovative applications in various fields, such as healthcare, finance, and transportation. At the heart of this transformation lie two core approaches: supervised and unsupervised machine learning. Understanding the differences …
What Are Gradients? Gradients are simply the mathematical representation of how much a given parameter, like weights in a neural network, affects the output of the model. In other words, gradients tell us how to adjust the parameters to minimize the error (or maximize the …
