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Machine Learning with Python Cookbook : practical solutions from preprocessing to deep learning /

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...

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Detalles Bibliográficos
Clasificación:	Libro Electrónico
Autor principal:	Gallatin, Kyle
Otros Autores:	Albon, Chris
Formato:	Electrónico eBook
Idioma:	Inglés
Publicado:	Sebastopol, CA : O'Reilly Media, Inc, 2023.
Edición:	Second edition.
Temas:	Machine learning. Python (Computer program language) Data mining. Apprentissage automatique. Python (Langage de programmation) Exploration de données (Informatique)
Acceso en línea:	Texto completo (Requiere registro previo con correo institucional)

Tabla de Contenidos:

Cover
Copyright
Table of Contents
Preface
Conventions Used in This Book
Using Code Examples
O'Reilly Online Learning
How to Contact Us
Acknowledgments
Chapter 1. Working with Vectors, Matrices, and Arrays in NumPy
1.0 Introduction
1.1 Creating a Vector
Problem
Solution
Discussion
See Also
1.2 Creating a Matrix
Problem
Solution
Discussion
See Also
1.3 Creating a Sparse Matrix
Problem
Solution
Discussion
See Also
1.4 Preallocating NumPy Arrays
Problem
Solution
Discussion
1.5 Selecting Elements
Problem
Solution
Discussion
1.6 Describing a Matrix
Problem
Solution
Discussion
1.7 Applying Functions over Each Element
Problem
Solution
Discussion
1.8 Finding the Maximum and Minimum Values
Problem
Solution
Discussion
1.9 Calculating the Average, Variance, and Standard Deviation
Problem
Solution
Discussion
1.10 Reshaping Arrays
Problem
Solution
Discussion
1.11 Transposing a Vector or Matrix
Problem
Solution
Discussion
1.12 Flattening a Matrix
Problem
Solution
Discussion
1.13 Finding the Rank of a Matrix
Problem
Solution
Discussion
See Also
1.14 Getting the Diagonal of a Matrix
Problem
Solution
Discussion
1.15 Calculating the Trace of a Matrix
Problem
Solution
Discussion
See Also
1.16 Calculating Dot Products
Problem
Solution
Discussion
See Also
1.17 Adding and Subtracting Matrices
Problem
Solution
Discussion
1.18 Multiplying Matrices
Problem
Solution
Discussion
See Also
1.19 Inverting a Matrix
Problem
Solution
Discussion
See Also
1.20 Generating Random Values
Problem
Solution
Discussion
Chapter 2. Loading Data
2.0 Introduction
2.1 Loading a Sample Dataset
Problem
Solution
Discussion
See Also
2.2 Creating a Simulated Dataset
Problem
Solution
Discussion
See Also
2.3 Loading a CSV File
Problem
Solution
Discussion
2.4 Loading an Excel File
Problem
Solution
Discussion
2.5 Loading a JSON File
Problem
Solution
Discussion
See Also
2.6 Loading a Parquet File
Problem
Solution
Discussion
See Also
2.7 Loading an Avro File
Problem
Solution
Discussion
See Also
2.8 Querying a SQLite Database
Problem
Solution
Discussion
See Also
2.9 Querying a Remote SQL Database
Problem
Solution
Discussion
See Also
2.10 Loading Data from a Google Sheet
Problem
Solution
Discussion
See Also
2.11 Loading Data from an S3 Bucket
Problem
Solution
Discussion
See Also
2.12 Loading Unstructured Data
Problem
Solution
Discussion
See Also
Chapter 3. Data Wrangling
3.0 Introduction
3.1 Creating a Dataframe
Problem
Solution
Discussion
3.2 Getting Information about the Data
Problem

Machine Learning with Python Cookbook : practical solutions from preprocessing to deep learning /

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