Welcome to a straightforward guide on machine learning. This paper is a summary that breaks down the big ideas of machine learning into easy-to-understand parts. Think of it as a quick reference or a cheat sheet that helps you come to grips with how machines learn to make sense of data, make predictions, and even create new things. We’ll look at different ways machines can be taught, how they figure out patterns on their own, and how they make smart decisions. Whether you’re new to the world of AI or just need a refresher, this paper aims to make the complex world of machine learning a little easier to navigate.
Supervised
Supervised Learning involves training algorithms with labeled data, where each input is paired with the correct output. This method teaches algorithms to map inputs to outputs, learning from clear examples. As it processes more data, the algorithm recognizes patterns and improves its predictions for new, unseen data.
Supervised