Machine Learning Python Cookbook by Gallatin Kyle (32 results)
- Softcover
Seller: BooksRun, Philadelphia, PA, U.S.A.BooksRun
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Paperback. Condition: 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.
- Softcover
Seller: Goodwill of Silicon Valley, SAN JOSE, CA, U.S.A.Goodwill of Silicon Valley
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Condition: good. Supports Goodwill of Silicon Valley job training programs. The cover and pages are in Good condition! Any other included accessories are also in Good condition showing use. Use can include some highlighting and writing, page and cover creases as well as other types visible wear.
- Softcover
Seller: Books From California, Simi Valley, CA, U.S.A.Books From California
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paperback. Condition: Very Good.
- Softcover
Seller: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
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- Softcover
Seller: BargainBookStores, Grand Rapids, MI, U.S.A.BargainBookStores
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Paperback or Softback. Condition: New. Machine Learning with Python Cookbook: Practical Solutions from Preprocessing to Deep Learning. Book.
- Softcover
Seller: PBShop.store US, Wood Dale, IL, U.S.A.PBShop.store US
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PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.
- Softcover
Seller: Rarewaves USA, OSWEGO, IL, U.S.A.Rarewaves USA
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US$ 61.69
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Paperback. Condition: 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 load…ing 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.
- Softcover
Seller: WorldofBooks, Goring-By-Sea, WS, United KingdomWorldofBooks
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US$ 58.28
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Paperback. Condition: Very Good. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.
- Softcover
Seller: California Books, Miami, FL, U.S.A.California Books
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Condition: New.
- Softcover
Seller: Brook Bookstore On Demand, Napoli, NA, ItalyBrook Bookstore On Demand
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Condition: new.
- Softcover
Seller: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail
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US$ 74.90
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Paperback. Condition: new. Paperback. 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, from loading d…ata 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 that 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 neighborsSupporting vector machines (SVM), naaeve Bayes, clustering, and tree-based modelsSaving, loading, and serving trained models from multiple frameworks About the Author Kyle Gallatin is a software engineer for machine learning infrastructure with years of experience as a data analyst, data scientist and machine learning engineer. He is also a professional data science mentor, volunteer computer science teacher and frequently publishes articles at the intersection of software engineering and machine learning. Currently, Kyle is a software engineer on the machine learning platform team at Etsy. Chris Albon is the Director of Machine Learning at the Wikimedia Foundation, the non-profit that hosts Wikipedia. This practical guide provides more than 200 self-contained recipes to help you solve machine learning challenges you may encounter in your work. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
- Softcover
Seller: Rarewaves.com USA, London, LONDO, United KingdomRarewaves.com USA
Contact seller5-star sellerCondition: New
US$ 76.12
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Paperback. Condition: 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 load…ing 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.
- Softcover
Seller: medimops, Berlin, Germanymedimops
Contact seller5-star sellerCondition: Used - As new
US$ 55.56
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Condition: as new. Wie neu/Like new.
- Softcover
Seller: GreatBookPricesUK, Woodford Green, United KingdomGreatBookPricesUK
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US$ 59.49
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Condition: New.
- Softcover
Seller: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
Contact seller5-star sellerCondition: Used - As new
US$ 76.02
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Condition: As New. Unread book in perfect condition.
- Softcover
Seller: GreatBookPricesUK, Woodford Green, United KingdomGreatBookPricesUK
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US$ 61.90
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Condition: As New. Unread book in perfect condition.
- Softcover
Seller: Ria Christie Collections, Uxbridge, United KingdomRia Christie Collections
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Condition: New. In.
- Softcover
Seller: Chiron Media, Wallingford, United KingdomChiron Media
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US$ 65.34
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Paperback. Condition: New.
- Softcover
Seller: Kennys Bookshop and Art Galleries Ltd., Galway, GY, IrelandKennys Bookshop and Art Galleries Ltd.
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US$ 75.92
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Condition: New. 2023. 2nd Edition. Paperback. . . . . .
- Softcover
Seller: THE SAINT BOOKSTORE, Southport, United KingdomTHE SAINT BOOKSTORE
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US$ 72.48
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Paperback / softback. Condition: New. New copy - Usually dispatched within 4 working days.
- Softcover
Seller: Kennys Bookstore, Olney, MD, U.S.A.Kennys Bookstore
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Condition: New. 2023. 2nd Edition. Paperback. . . . . . Books ship from the US and Ireland.
- Softcover
Seller: Majestic Books, Hounslow, United KingdomMajestic Books
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Condition: New.
- Softcover
Seller: Revaluation Books, Exeter, United KingdomRevaluation Books
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Paperback. Condition: Brand New. 2nd edition. 380 pages. 9.19x7.00x0.85 inches. In Stock.
- Softcover
Seller: Speedyhen, Hertfordshire, United KingdomSpeedyhen
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Condition: NEW.
- Softcover
Seller: Rarewaves USA United, OSWEGO, IL, U.S.A.Rarewaves USA United
Contact seller5-star sellerCondition: New
US$ 65.87
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Paperback. Condition: 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 load…ing 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.
- Softcover
Seller: Books Puddle, New York, NY, U.S.A.Books Puddle
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Condition: New.
- Softcover
Seller: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller
Contact seller5-star sellerCondition: New
US$ 87.27
US$ 37.00 shippingShips from Australia to U.S.A.Quantity: 1 available
Paperback. Condition: new. Paperback. 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, from loading d…ata 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 that 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 neighborsSupporting vector machines (SVM), naaeve Bayes, clustering, and tree-based modelsSaving, loading, and serving trained models from multiple frameworks About the Author Kyle Gallatin is a software engineer for machine learning infrastructure with years of experience as a data analyst, data scientist and machine learning engineer. He is also a professional data science mentor, volunteer computer science teacher and frequently publishes articles at the intersection of software engineering and machine learning. Currently, Kyle is a software engineer on the machine learning platform team at Etsy. Chris Albon is the Director of Machine Learning at the Wikimedia Foundation, the non-profit that hosts Wikipedia. This practical guide provides more than 200 self-contained recipes to help you solve machine learning challenges you may encounter in your work. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
- Softcover
Seller: preigu, Osnabrück, Germanypreigu
Contact seller5-star sellerCondition: New
US$ 76.24
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Taschenbuch. Condition: Neu. Machine Learning with Python Cookbook | Practical Solutions from Preprocessing to Deep Learning | Kyle Gallatin (u. a.) | Taschenbuch | Englisch | 2023 | O'Reilly Media | EAN 9781098135720 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbie…ter: preigu.
- Softcover
Seller: Rarewaves.com UK, London, United KingdomRarewaves.com UK
Contact seller5-star sellerCondition: New
US$ 73.05
US$ 88.08 shippingShips from United Kingdom to U.S.A.Quantity: Over 20 available
Paperback. Condition: 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 load…ing 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.
- Softcover
Seller: BestAroundDeals, Grand Rapids, MI, U.S.A.BestAroundDeals
Contact seller5-star sellerCondition: New
US$ 179.39
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Soft cover. Condition: New. 2nd Edition.
