CrazyLearners🙂

  The  K-Nearest Neighbor (KNN)  algorithm is one of the simplest yet powerful supervised learning techniques used for classification and regression tasks in  machine learning . Understanding KNN is crucial for beginners as it provides insights into core concepts such as distance metrics and data point classification. What is the K-Nearest Neighbor (KNN) Algorithm? K-Nearest Neighbor (KNN) is a  supervised learning algorithm  used for both  classification  and  regression . It is non-parametric, meaning it doesn’t make any assumptions about the underlying data distribution, which makes it versatile for various applications. KNN works by analyzing the proximity or “closeness” of data points based on specific distance metrics. In  classification , KNN assigns a class label to a new data point based on the majority class of its nearest neighbors. For instance, if a data point has five nearest neighbors, and three of them belong to cla...

  UNIT- 1   Syllabus: Introduction - Well-posed learning problems, designing a learning system, Perspectives and issues in machine learning. Concept learning and the general to specific ordering – introduction, a concept learning task, concept learning as search, find-S: finding a maximally specific hypothesis, version spaces and the candidate elimination algorithm, remarks on version spaces and candidate elimination, inductive bias, Gradient Descent Algorithm and its variants. What Is Machine Learning? In the real world, we are surrounded by humans who can learn everything from their experiences with their learning capability, and we have computers or machines which work on our instructions. But can a machine also learn from experiences or past data like a human does? So here comes the role of Machine Learning .       What is learning? Learning is any pr...