In recent years, the field of machine learning has experienced exponential growth, with applications in diverse domains such as healthcare, finance, and automation. One of the most promising areas of development is TinyML, which brings machine learning to resource-constrained devices. We will explore the concept of TinyML, its applications, and its potential to

We will explain the main differences between neural networks and deep learning Since their inception in the late 1950s, Artificial Intelligence and machine learning have come a long way. These technologies are now extremely advanced and sophisticated. However, even though technological advancements in the field of data science are to be commended, they have

Today, deep learning is the talk of the town. There is no shortage of media coverage, papers, books, and events on deep learning. Yet deep learning is not new. Its roots go back almost to the early days of artificial intelligence and computing. While the field received the cold shoulder

Property valuation is a critical aspect of the real estate industry. Accurate property valuations are essential for mortgage lending, insurance, property tax assessment, and investment analysis. Historically, property valuations were done by trained professionals who would visit the property, assess its condition and location, and consider comparable properties in the area. With

With all the hype around AI, especially generative AI chatbots, the topic is getting a lot more attention from businesses and the general public. Machine learning (ML), especially deep learning and generative ML, are a big driver of these developments. A sober analysis of AI in business contexts, however, reveals