The field of machine learning has experienced a strong expansion in recent years, mostly driven by the development of new computational methods and the unprecedented surge in the volume of data accessible for processing and analysis. This dynamic has opened up new frontiers for exploration and innovation in many different areas. In this presentation we will provide a general overview of machine learning, offering insight into its most important areas and unveiling some key application domains, such as computer vision and natural language processing.
Deep learning is a subfield of machine learning that involves the use of artificial neural networks to automatically learn and extract intricate features from vast datasets. The perceptron was proposed in 1957 and is the simplest form of neural network. The original perceptron evolved over time, contributing to the creation of large and versatile architectures with widespread applications across various domains.