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 …
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. …
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 …
Random forests may sound like a strange term, but in the world of data science and machine learning, they are a powerful and versatile tool. In this article, we’ll break down the concept of random forests in simple terms, making it easy for anyone to …
Machine learning is a rapidly growing field that allows computers to learn and make predictions based on data. At the heart of machine learning are various models that enable these tasks. In this article, we’ll explore some of the most popular machine learning models, including …
When working with data, especially in the realm of machine learning, it’s essential to understand how to prepare and manipulate the data to achieve better results. This process, known as feature engineering, involves transforming, reducing, and selecting features within your dataset to improve the performance …
Machine learning has undeniably made remarkable strides in recent years, enabling algorithms to learn from data and make predictions with unprecedented accuracy. However, there’s a critical problem that continues to plague the field: catastrophic forgetting, also known as catastrophic interference. This phenomenon occurs when machine …
