Machine Learning with Python Cookbook: Practical Solutions from Preprocessing to

Description: Machine Learning with Python Cookbook by Kyle Gallatin, Chris Albon This practical guide provides more than 200 self-contained recipes to help you solve machine learning challenges you may encounter in your work. FORMAT Paperback CONDITION Brand New Publisher Description This practical guide provides more than 200 self-contained recipes to help you solve machine learning challenges you may encounter in your work. If youre comfortable with Python and its libraries, including pandas and scikit-learn, youll 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. Youll 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), naäve 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. Author Biography 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. Details ISBN1098135725 Author Chris Albon Pages 380 Publisher OReilly Media Year 2023 Edition 2nd ISBN-13 9781098135720 Format Paperback Imprint OReilly Media Subtitle Practical Solutions from Preprocessing to Deep Learning Place of Publication Sebastopol Country of Publication United States AU Release Date 2023-10-31 NZ Release Date 2023-10-31 UK Release Date 2023-10-31 ISBN-10 1098135725 Edition Description 2nd Revised edition Publication Date 2023-08-11 US Release Date 2023-08-11 DEWEY 006.31 We've got this At The Nile, if you're looking for it, we've got it. With fast shipping, low prices, friendly service and well over a million items - you're bound to find what you want, at a price you'll love! TheNile_Item_ID:143170619;

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