| Titre : | Machine Learning for Industrial Applications/ Prakach, Kolla Bhanu |
| Type de document : | texte imprimé |
| Editeur : | Hoboken, NJ : Wiley, 2024 |
| ISBN/ISSN/EAN : | 978-1-394-26896-2 |
| Format : | 352 p. / tab., fig., sch. / 24 cm |
| Langues: | Anglais |
| Mots-clés: | Machine Learning ; algorithm ; industrial applications ; technology ; clustering ; reinforcement learning ; recommender systems ; distance-based models |
| Résumé : |
A brief overview of key themes and insights:
Foundational Algorithms: The book devotes significant chapters to classical ML methods: linear models, rule‑based systems, kernel methods (like support vector machines), clustering, ensembles, etc. These are the foundational “building blocks” that underpin more applied work. Deep Learning & Modern Techniques: It then moves into advanced deep‑learning methods, including implementation using Julia. This indicates an intent to give the reader hands‑on tools and somewhat more cutting‑edge approaches. Practical Orientation: A strong emphasis on application, not just theory. The description mentions numerous examples, exercises, and real‑world case studies to reinforce practical skills. Industrial Application Focus: The final chapter (16) is dedicated to “Machine Learning for Industrial Applications”. This indicates the book closes by connecting all the algorithmic and methodological material back into an industrial environment: manufacturing, production, logistics, etc. Accessible Coverage: The description highlights that the book aims to "demystify" machine learning, making it accessible to a wide audience. Thus, it’s likely to include intuitive explanations, rather than deep mathematically rigorous derivations. |
Exemplaires (2)
| Code-barres | Cote | Support | Localisation | Section | Disponibilité |
|---|---|---|---|---|---|
| 139426896201 | 006.31/01 | Livre | Bibliothèque Estin | Documentaires | Consultation sur place Exclu du prêt |
| 139426896202 | 006.31/01.2 | Livre | Bibliothèque Estin | Documentaires | Disponible |
