Machine Learning with Python Cookbook

Practical Solutions from Preprocessing to Deep Learning

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Beschreibung

<p>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.</p><p>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.</p><p>Go beyond theory and concepts by learning the nuts and bolts you need to construct working machine learning applications. You'll find recipes for:</p><ul> • Vectors, matrices, and arrays • Working with data from CSV, JSON, SQL, databases, cloud storage, and other sources • Handling numerical and categorical data, text, images, and dates and times • Dimensionality reduction using feature extraction or feature selection • Model evaluation and selection • Linear and logical regression, trees and forests, and k-nearest neighbors • Supporting vector machines (SVM), naäve Bayes, clustering, and tree-based models • Saving, loading, and serving trained models from multiple frameworks</ul>

Artikeldetails

EAN

9781098135720

Sprache

Englisch

Einband / Art

Taschenbuch

Maße

229 x 175 x 24 mm

Erscheinungsjahr

2023

Verlag / Hersteller

O'Reilly Media