Introduction Machine learning algorithms can be broadly categorized into Instance-Based Learning and Model-Based Learning. Understanding these approaches is crucial for selecting the right algorithm for a given task. This tutorial explores the fundamental differences between these two paradigms, their advantages, and real-world use cases. Instance-Based Learning: These algorithms memorize the training data. When a new…

1. Introduction In the world of machine learning, models learn from data to make predictions or decisions. The way this learning happens can be broadly categorized into two main approaches: offline (batch) learning and online learning. 2. What is Batch Machine Learning? Batch machine learning refers to training a model on a fixed dataset that…

1. Introduction In this tutorial, we’ll discuss different types of machine learning. Different types of machine learning can be shown with the help of following figure: 2. Supervised machine learning Supervised machine learning is a type of machine learning where an algorithm is trained on a labeled dataset, meaning the data includes both the input…

1. Artificial intelligence Artificial intelligence (AI) refers to the capability of machines, especially computer systems, to demonstrate intelligence. It is a branch of computer science focused on creating and studying methods and software that allow machines to understand their environment and make decisions by learning and adapting. These intelligent systems aim to take actions that…