Editore: O'Reilly Media (edition 2), 2023
ISBN 10: 1098135725 ISBN 13: 9781098135720
Lingua: Inglese
Da: BooksRun, Philadelphia, PA, U.S.A.
Paperback. Condizione: Very Good. 2. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.
paperback. Condizione: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!
Condizione: New.
Condizione: As New. Unread book in perfect condition.
Paperback. Condizione: New. 2nd. This practical guide provides more than 200 self-contained recipes to help you solve machine learning challenges you may encounter in your work. If you're comfortable with Python and its libraries, including pandas and scikit-learn, you'll be able to address specific problems all the way from loading data to training models and leveraging neural networks.Each recipe in this updated edition includes code that you can copy, paste, and run with a toy dataset to ensure it works. From there, you can adapt these recipes according to your use case or application. Recipes include a discussion that explains the solution and provides meaningful context. Go beyond theory and concepts by learning the nuts and bolts you need to construct working machine learning applications.You'll find recipes for:Vectors, matrices, and arraysWorking with data from CSV, JSON, SQL, databases, cloud storage, and other sourcesHandling numerical and categorical data, text, images, and dates and timesDimensionality reduction using feature extraction or feature selectionModel evaluation and selectionLinear and logical regression, trees and forests, and k-nearest neighborsSupport vector machines (SVM), naive Bayes, clustering, and tree-based modelsSaving and loading trained models from multiple frameworks.
Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 49,93
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New.
Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 56,38
Quantità: 3 disponibili
Aggiungi al carrelloCondizione: New. In.
Da: Chiron Media, Wallingford, Regno Unito
EUR 54,85
Quantità: 4 disponibili
Aggiungi al carrelloPaperback. Condizione: New.
EUR 74,45
Quantità: 2 disponibili
Aggiungi al carrelloPaperback. Condizione: New. 2nd. This practical guide provides more than 200 self-contained recipes to help you solve machine learning challenges you may encounter in your work. If you're comfortable with Python and its libraries, including pandas and scikit-learn, you'll be able to address specific problems all the way from loading data to training models and leveraging neural networks.Each recipe in this updated edition includes code that you can copy, paste, and run with a toy dataset to ensure it works. From there, you can adapt these recipes according to your use case or application. Recipes include a discussion that explains the solution and provides meaningful context. Go beyond theory and concepts by learning the nuts and bolts you need to construct working machine learning applications.You'll find recipes for:Vectors, matrices, and arraysWorking with data from CSV, JSON, SQL, databases, cloud storage, and other sourcesHandling numerical and categorical data, text, images, and dates and timesDimensionality reduction using feature extraction or feature selectionModel evaluation and selectionLinear and logical regression, trees and forests, and k-nearest neighborsSupport vector machines (SVM), naive Bayes, clustering, and tree-based modelsSaving and loading trained models from multiple frameworks.
Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 59,17
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
Da: Majestic Books, Hounslow, Regno Unito
EUR 69,77
Quantità: 3 disponibili
Aggiungi al carrelloCondizione: New.
EUR 39,95
Quantità: 1 disponibili
Aggiungi al carrelloCondizione: Neuf.
Da: Biblios, Frankfurt am main, HESSE, Germania
EUR 79,43
Quantità: 3 disponibili
Aggiungi al carrelloCondizione: New.
Da: Revaluation Books, Exeter, Regno Unito
EUR 79,78
Quantità: 2 disponibili
Aggiungi al carrelloPaperback. Condizione: Brand New. 2nd edition. 380 pages. 9.19x7.00x0.85 inches. In Stock.
Da: Books Puddle, New York, NY, U.S.A.
Condizione: New.
EUR 61,60
Quantità: Più di 20 disponibili
Aggiungi al carrelloPaperback. Condizione: New. 2nd. This practical guide provides more than 200 self-contained recipes to help you solve machine learning challenges you may encounter in your work. If you're comfortable with Python and its libraries, including pandas and scikit-learn, you'll be able to address specific problems all the way from loading data to training models and leveraging neural networks.Each recipe in this updated edition includes code that you can copy, paste, and run with a toy dataset to ensure it works. From there, you can adapt these recipes according to your use case or application. Recipes include a discussion that explains the solution and provides meaningful context. Go beyond theory and concepts by learning the nuts and bolts you need to construct working machine learning applications.You'll find recipes for:Vectors, matrices, and arraysWorking with data from CSV, JSON, SQL, databases, cloud storage, and other sourcesHandling numerical and categorical data, text, images, and dates and timesDimensionality reduction using feature extraction or feature selectionModel evaluation and selectionLinear and logical regression, trees and forests, and k-nearest neighborsSupport vector machines (SVM), naive Bayes, clustering, and tree-based modelsSaving and loading trained models from multiple frameworks.
EUR 69,48
Quantità: 2 disponibili
Aggiungi al carrelloPaperback. Condizione: New. 2nd. This practical guide provides more than 200 self-contained recipes to help you solve machine learning challenges you may encounter in your work. If you're comfortable with Python and its libraries, including pandas and scikit-learn, you'll be able to address specific problems all the way from loading data to training models and leveraging neural networks.Each recipe in this updated edition includes code that you can copy, paste, and run with a toy dataset to ensure it works. From there, you can adapt these recipes according to your use case or application. Recipes include a discussion that explains the solution and provides meaningful context. Go beyond theory and concepts by learning the nuts and bolts you need to construct working machine learning applications.You'll find recipes for:Vectors, matrices, and arraysWorking with data from CSV, JSON, SQL, databases, cloud storage, and other sourcesHandling numerical and categorical data, text, images, and dates and timesDimensionality reduction using feature extraction or feature selectionModel evaluation and selectionLinear and logical regression, trees and forests, and k-nearest neighborsSupport vector machines (SVM), naive Bayes, clustering, and tree-based modelsSaving and loading trained models from multiple frameworks.
Editore: First interactive (5/2024), 2024
ISBN 10: 2412094438 ISBN 13: 9782412094433
Lingua: Francese
Da: BOOKIT!, Genève, Svizzera
EUR 81,59
Quantità: 1 disponibili
Aggiungi al carrelloCondizione: Used: Like New. LIVRE A L?ETAT DE NEUF. EXPEDIE SOUS 3 JOURS OUVRES. NUMERO DE SUIVI COMMUNIQUE AVANT ENVOI, EMBALLAGE RENFORCE. EAN:9782412094433.
EUR 26,60
Quantità: 1 disponibili
Aggiungi al carrelloCondizione: Gut. Zustand: Gut | Sprache: Französisch | Produktart: Bücher.
Da: Revaluation Books, Exeter, Regno Unito
EUR 71,13
Quantità: 2 disponibili
Aggiungi al carrelloPaperback. Condizione: Brand New. 2nd edition. 380 pages. 9.19x7.00x0.85 inches. In Stock. This item is printed on demand.