Python kikai gakushū kukkubukku

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 loadin...

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Bibliographic Details
Other Authors: Albon, Chris, author (author), Gallatin, Kyle, author (translator), Nakada, Hidemoto, translator
Format: eBook
Language:Japonés
Published: Tōkyō-to Shinjuku-ku : Orairī Japan 2024.
Edition:Dai 2-han
Subjects:
See on Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009851338906719
Description
Summary: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 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 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.
Physical Description:1 online resource (428 pages)
ISBN:9784814400843