| Titre : | Machine learning design patterns : solutions to common challenges in data preparation, model building, and MLOps |
| Auteurs : | Valliappa Lakshmanan, Auteur ; Sara Robinson, Auteur ; Michael Munn, Auteur |
| Type de document : | texte imprimé |
| Editeur : | Sebastopol [Etats-Unis] : O'Reilly Media, 2021 |
| ISBN/ISSN/EAN : | 978-1-09-811578-4 |
| Format : | XIV, 390 p. / ill. / 24 cm |
| Note générale : | Index |
| Langues : | Anglais |
| Index. décimale : | 004.8 (Intelligence artificielle) |
| Tags : | Machine learning Computer programming Big data Apprentissage automatique Design patterns |
| Résumé : | n this book, you will find detailed explanations of 30 patterns for data and problem representation, operationalization, repeatability, reproducibility, flexibility, explainability, and fairness. Each pattern includes a description of the problem, a variety of potential solutions, and recommendations for choosing the best technique for your situation. |
| Note de contenu : |
Summary :
1. The need for machine learning design patterns. 2. Data representation design patterns. 3. Problem representation design patterns. 4. Model training patterns. 5. Design patterns for resilient serving. 6. Reproducibility design patterns. 7. Responsible AI. 8. Connected patterns. |
Exemplaires (3)
| Cote | Support | Localisation | Section | Disponibilité | Etat_Exemplaire |
|---|---|---|---|---|---|
| 004.8 LAK | Papier | Bibliothèque Centrale | Informatique | Disponible | Consultation sur place |
| 004.8 LAK | Papier | Bibliothèque Centrale | Informatique | Disponible | En bon état |
| 004.8 LAK | Papier | Bibliothèque Centrale | Informatique | Disponible | En bon état |
