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LEARN Scikit-Learn: Essential Machine Learning for Data Science (AI & Machine Learning ENG) - Tapa blanda
Sinopsis
LEARN Scikit-Learn: Essential Machine Learning for Data Science
This book is the key to mastering Scikit-Learn and building market-ready Machine Learning projects. Ideal for professionals and students who seek fast, direct, and applicable results. Learn high-impact techniques, design intelligent solutions, and boost your career in data science.
Includes:
• Quick setup of a productive environment with Python and Scikit-Learn
• Data preprocessing and full pipeline automation
• Fine-tuning models with cross-validation and hyperparameters
• Practical application of regression, classification, and clustering
• Model deployment integrated with Big Data and MLOps environments
Master the most widely used algorithms in the market and accelerate your entry into data science projects with Scikit-Learn.
scikit-learn, machine learning, data science, smart pipelines, model automation, cross-validation, machine learning deployment, big data integration, mlops, spark
"Sinopsis" puede pertenecer a otra edición de este libro.
- EditorialIndependently published
- Año de publicación2025
- ISBN 13 9798281460163
- EncuadernaciónTapa blanda
- IdiomaInglés
- Número de páginas208
- Contacto del fabricanteno disponible
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LEARN Scikit-Learn: Essential Machine Learning for Data Science (AI & Machine Learning ENG)
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LEARN Scikit-Learn: Essential Machine Learning for Data Science (AI & Machine Learning ENG)
Impresión bajo demandaLibrería: California Books, Miami, FL, Estados Unidos de America
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LEARN Scikit-Learn (Paperback)
Librería: CitiRetail, Stevenage, Reino Unido
Calificación del vendedor: 5 de 5 estrellas
Paperback. Condición: new. Paperback. LEARN Scikit-Learn: Essential Machine Learning for Data ScienceThis book is the key to mastering Scikit-Learn and building market-ready Machine Learning projects. Ideal for professionals and students who seek fast, direct, and applicable results. Learn high-impact techniques, design intelligent solutions, and boost your career in data science.Includes: - Quick setup of a productive environment with Python and Scikit-Learn- Data preprocessing and full pipeline automation- Fine-tuning models with cross-validation and hyperparameters- Practical application of regression, classification, and clustering- Model deployment integrated with Big Data and MLOps environmentsMaster the most widely used algorithms in the market and accelerate your entry into data science projects with Scikit-Learn.scikit-learn, machine learning, data science, smart pipelines, model automation, cross-validation, machine learning deployment, big data integration, mlops, spark Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Nº de ref. del artículo: 9798281460163
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LEARN Scikit-Learn (Paperback)
Librería: Grand Eagle Retail, Fairfield, OH, Estados Unidos de America
Calificación del vendedor: 5 de 5 estrellas
Paperback. Condición: new. Paperback. LEARN Scikit-Learn: Essential Machine Learning for Data ScienceThis book is the key to mastering Scikit-Learn and building market-ready Machine Learning projects. Ideal for professionals and students who seek fast, direct, and applicable results. Learn high-impact techniques, design intelligent solutions, and boost your career in data science.Includes: - Quick setup of a productive environment with Python and Scikit-Learn- Data preprocessing and full pipeline automation- Fine-tuning models with cross-validation and hyperparameters- Practical application of regression, classification, and clustering- Model deployment integrated with Big Data and MLOps environmentsMaster the most widely used algorithms in the market and accelerate your entry into data science projects with Scikit-Learn.scikit-learn, machine learning, data science, smart pipelines, model automation, cross-validation, machine learning deployment, big data integration, mlops, spark Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Nº de ref. del artículo: 9798281460163
Cantidad disponible: 1 disponibles