Publication

Probing the Past with Data Analytics and AI

2025

Abstract

This comprehensive compendium explains the technical challenges and opportunities behind the most recent and successful applications in artificial intelligence [AI] and data analytics. It focuses on applications that have the power to be adapted to many different fields and explains how AI can be implemented as an assistant in digital humanities. It also introduces new methods and applications in classification trees, networks, and Bayesian learning. The useful reference text benefits professionals, academics, researchers, and graduate students in AI/machine learning, neural networks, and bioinformatics, and digital humanities.

Official source

https://infoscience.epfl.ch/entities/publication/a2b09246-3a1b-45f0-8f3c-565134f3ca8c

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2025

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/a2b09246-3a1b-45f0-8f3c-565134f3ca8c

About this result

Related concepts (31)

Artificial intelligence

Artificial intelligence (AI) is the intelligence of machines or software, as opposed to the intelligence of human beings or animals. AI applications include advanced web search engines (e.g., Google Search), recommendation systems (used by YouTube, Amazon, and Netflix), understanding human speech (such as Siri and Alexa), self-driving cars (e.g., Waymo), generative or creative tools (ChatGPT and AI art), and competing at the highest level in strategic games (such as chess and Go).

Applications of artificial intelligence

Artificial intelligence (AI) has been used in applications to alleviate certain problems throughout industry and academia. AI, like electricity or computers, is a general purpose technology that has a multitude of applications. It has been used in fields of language translation, image recognition, credit scoring, e-commerce and other domains. Recommendation system A recommendation system predicts the "rating" or "preference" a user would give to an item.

Artificial neural network

Artificial neural networks (ANNs, also shortened to neural networks (NNs) or neural nets) are a branch of machine learning models that are built using principles of neuronal organization discovered by connectionism in the biological neural networks constituting animal brains. An ANN is based on a collection of connected units or nodes called artificial neurons, which loosely model the neurons in a biological brain. Each connection, like the synapses in a biological brain, can transmit a signal to other neurons.

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