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This book, which arises from the teaching experience of the authors, provides an agile overview of the different Artificial Intelligence technologies.
Artificial Intelligence is a multidisciplinary field which originates from diversified disciplines, from data science to statistics, from natural language processing to signal processing, and has produced different types of solutions, such as supervised, unsupervised, and semi-supervised learning, and technologies, including deep neural networks and generative artificial intelligence.
This book also provides an overview of the main use cases and maps them into the most suitable method.
To help readers get along, the book also includes references to specific application examples solved in popular open source libraries (such as scikit-learn and Keras) and includes references to key literature articles.
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This book, which arises from the teaching experience of the authors, provides an agile overview of the different Artificial Intelligence technologies.
Artificial Intelligence is a multidisciplinary field which originates from diversified disciplines, from data science to statistics, from natural language processing to signal processing, and has produced different types of solutions, such as supervised, unsupervised, and semi-supervised learning, and technologies, including deep neural networks and generative artificial intelligence.
This book also provides an overview of the main use cases and maps them into the most suitable method.
To help readers get along, the book also includes references to specific application examples solved in popular open source libraries (such as scikit-learn and Keras) and includes references to key literature articles.