Machine Learning for Industrial Applications

1Overview of Machine Learning

1.1 Introduction

Machine learning is a branch of artificial intelligence (AI) that focuses on developing algorithms and models that enable computers to learn and make predictions or decisions without being explicitly programmed. It is a field that has gained significant attention and prominence due to its ability to solve complex problems and make sense of large amounts of data.

Machine learning teaches computers how to learn from data and improve their performance over time. This is achieved through various techniques and algorithms that allow machines to recognize patterns, make predictions, and adapt their behavior based on their input.

There are several key concepts and components within machine learning:

Data: Data are the foundation of machine learning. Algorithms learn from data, which can be in the form of text, images, videos, numerical values, or any other structured or unstructured format.

Features: Features are the attributes or characteristics of the data that are used by algorithms to make predictions or classifications. Selecting relevant features is crucial for the success of a machine learning model.

Labels: In supervised learning, which is a common type of machine learning, data are labeled with the correct output. The algorithm learns from the labeled data to predict new, unseen data.

Algorithms: Machine learning algorithms are mathematical models that process and learn from data. These algorithms can be categorized into different ...