Large Language Models (LLMs): Simply but Faithfully explained - Couverture souple

Bernas, Yves

Couverture souple

ISBN 13 : 9798248763696

Editeur : Independently published, 2026

Synopsis

Large Language Models (LLMs) have become a central technology of modern AI — yet most explanations remain either overly technical, vague, or buried under metaphors.
This book offers a clear and rigorous introduction to how LLMs actually work, using only standard school-level mathematics and avoiding misleading simplifications. It answers the questions that many tutorials skip: how neural networks can perform prediction, why pattern-matching scores can be interpreted as probabilities, what embeddings really represent, and what the Query–Key–Value mechanism is truly doing inside a Transformer.
Starting from the early Bengio-style neural language model, the book gradually builds up the essential concepts — forward neural networks, feature recognition, logits, softmax, gradient descent — before reaching the Transformer architecture and its attention mechanism.
Written for curious readers without a machine-learning background, this is an accessible but faithful journey into the foundations of today’s language models.
If you want to understand LLMs without handwaving, buzzwords, or empty metaphors, this book is for you.

Détails de l'édition

• Éditeur: Independently published
• Date d'édition: 2026
• Langue: anglais
• ISBN 13: 9798248763696
• Reliure: Broché
• Nombre de pages: 110
• Coordonnées du fabricant: Manufactured by Amazon on behalf of the author; https://www.amazon.fr/hz/contact-us; ; c/o Amazon Media EU S.à.r.l., 38 Avenue John F. Kennedy; Luxembourg; L-1855; Luxembourg