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Machine Learning with Python Cookbook
Machine Learning with Python Cookbook
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A01=Chris Albon
A01=Kyle Gallatin
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AI artificial intelligence Python Machine Learning Scikit-learn Numpy Pandas Linear Regression Tree-based Models Random Forest Gradient Boosting NLP Deep Learning Tensorflow Keras
Author_Chris Albon
Author_Kyle Gallatin
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Category1=Non-Fiction
Category=UM
Category=UMX
Category=UYQ
Category=UYQM
Category=UYQN
COP=United States
Delivery_Delivery within 10-20 working days
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Language_English
PA=Available
Price_€50 to €100
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softlaunch
Product details
- ISBN 9781098135720
- Dimensions: 178 x 233mm
- Publication Date: 11 Aug 2023
- Publisher: O'Reilly Media
- Publication City/Country: US
- Product Form: Paperback
- Language: English
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 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
Support vector machines (SVM), naive Bayes, clustering, and tree-based models
Saving and loading trained models from multiple frameworks
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.
Machine Learning with Python Cookbook
€76.99
