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Machine Learning Pytorch Scikit Learn by Sebastian Raschka (28 results)
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Machine Learning with PyTorch and Scikit-Learn: Develop machine learning and deep learning models with Python (Paperback or Softback)
Published by Packt Publishing 2/25/2022, 2022
ISBN 10: 1801819319 ISBN 13: 9781801819312
Language: English
Paperback or Softback. Condition: New. Machine Learning with PyTorch and Scikit-Learn: Develop machine learning and deep learning models with Python 2.86. Book.
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Machine Learning with PyTorch and Scikit-Learn: Develop machine learning and deep learning models with Python
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Machine Learning with PyTorch and Scikit-Learn: Develop machine learning and deep learning models with Python
Published by Packt Publishing 2022-02, 2022
ISBN 10: 1801819319 ISBN 13: 9781801819312
Language: English
US$ 63.18
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Machine Learning with PyTorch and Scikit-Learn: Develop machine learning and deep learning models with Python
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Machine Learning with PyTorch and Scikit-Learn: Develop machine learning and deep learning models with Python
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paperback. Condition: Good. Textbook, May Have Highlights, Notes and/or Underlining, BOOK ONLY-NO ACCESS CODE, NO CD, Ships with Tracking.
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Add to basketCondition: New. Fully updated with PyTorch and the latest additions to scikit-learn. Packed with clear explanations, visualizations, and working examples, the book covers essential machine learning techniques in depth, along with two cutting-edge machine learning technique.
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Machine Learning with PyTorch and Scikit-Learn
Published by Packt Publishing Limited, 2022
ISBN 10: 1801819319 ISBN 13: 9781801819312
Language: English
PAP. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
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Machine Learning with PyTorch and Scikit-Learn
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Add to basketRustica (tapa blanda). Condition: New. Dust Jacket Condition: Nuevo. 01. Machine Learning con PyTorch y Scikit-Learn Si busca un manual de referencia sobre Machine Learning y Deep Learning con PyTorch, ha llegado al libro indicado. En él se explica paso a paso cómo construir sistemas de aprendizaje automático con éxito. Mientras que en algunos libros solo se enseña a seguir instrucciones, en este descubrirá los principios para crear modelos y aplicaciones por sí mismo. Encontrará multitud de explicaciones claras, visualizaciones y ejemplos, y aprenderá en profundidad todas las técnicas esenciales de Machine Learning. Actualizado para ocuparse de Machine Learning utilizando PyTorch, este libro también presenta las últimas incorporaciones a Scikit-Learn. Además, trata varias técnicas de Machine Learning y Deep Learning para la clasificación de textos e imágenes. Con este libro, también aprenderá sobre las redes generativas antagónicas (GAN), útiles para generar nuevos datos y entrenar agentes inteligentes con aprendizaje reforzado. Por último, esta edición incluye las últimas tendencias en Machine Learning, como las introducciones a las redes neuronales de grafos y transformadores a gran escala utilizados para el procesamiento del lenguaje natural (NLP). Sin duda, tanto si es un desarrollador de Python neófito en Machine Learning como si desea profundizar en los últimos avances, este libro de PyTorch será su gran aliado en el aprendizaje automático con Python. Estoy seguro de que este libro le resultará muy valioso, tanto por ofrecer una visión general del apasionante campo de Machine Learning, como por ser un tesoro de conocimientos prácticos. Espero que le inspire a aplicar Machine Learning para lograr un mayor beneficio, sea cual sea su problemática -Dmytro Dzhulgakov PyTorch Core Maintainer. LIBRO.
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MACHINE LEARNING CON PYTORCH Y SCIKIT LEARN
Published by MARCOMBO EDICIONES TECNICAS, 2023
ISBN 10: 8426735738 ISBN 13: 9788426735737
Language: Spanish
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Add to basketCondition: Nuevo. FORMACION - EMPRESA Y GESTION# PROGRAMACION INFORMATICA/DESARROLLO DE SOFTWAR# ALGORITMOS Y ESTRUCTURAS DE DATOS.
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MACHINE LEARNING CON PYTORCH Y SCIKIT LEARN
Published by MARCOMBO EDICIONES TECNICAS, España, 2023
ISBN 10: 8426735738 ISBN 13: 9788426735737
Language: Spanish
US$ 47.48
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Add to basketRústica. Condition: Nuevo. Dust Jacket Condition: Nuevo. AZTUNIV.
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Machine Learning with PyTorch and Scikit-Learn
Published by Packt Publishing, Limited, 2022
ISBN 10: 1801819319 ISBN 13: 9781801819312
Language: English
US$ 82.25
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Machine Learning with PyTorch and Scikit-Learn: Develop machine learning and deep learning models with Python
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Add to basketTaschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book of the bestselling and widely acclaimed Python Machine Learning series is a comprehensive guide to machine and deep learning using PyTorch's simple to code framework.Purchase of the print or Kindle book includes a free Elektronisches Buch in PDF format.Key FeaturesLearn applied machine learning with a solid foundation in theoryClear, intuitive explanations take you deep into the theory and practice of Python machine learningFully updated and expanded to cover PyTorch, transformers, XGBoost, graph neural networks, and best practicesBook DescriptionMachine Learning with PyTorch and Scikit-Learn is a comprehensive guide to machine learning and deep learning with PyTorch. It acts as both a step-by-step tutorial and a reference you'll keep coming back to as you build your machine learning systems.Packed with clear explanations, visualizations, and examples, the book covers all the essential machine learning techniques in depth. While some books teach you only to follow instructions, with this machine learning book, we teach the principles allowing you to build models and applications for yourself.Why PyTorch PyTorch is the Pythonic way to learn machine learning, making it easier to learn and simpler to code with. This book explains the essential parts of PyTorch and how to create models using popular libraries, such as PyTorch Lightning and PyTorch Geometric.You will also learn about generative adversarial networks (GANs) for generating new data and training intelligent agents with reinforcement learning. Finally, this new edition is expanded to cover the latest trends in deep learning, including graph neural networks and large-scale transformers used for natural language processing (NLP).This PyTorch book is your companion to machine learning with Python, whether you're a Python developer new to machine learning or want to deepen your knowledge of the latest developments.What you will learnExplore frameworks, models, and techniques for machines to 'learn' from dataUse scikit-learn for machine learning and PyTorch for deep learningTrain machine learning classifiers on images, text, and moreBuild and train neural networks, transformers, and boosting algorithmsDiscover best practices for evaluating and tuning modelsPredict continuous target outcomes using regression analysisDig deeper into textual and social media data using sentiment analysisWho this book is forIf you have a good grasp of Python basics and want to start learning about machine learning and deep learning, then this is the book for you. This is an essential resource written for developers and data scientists who want to create practical machine learning and deep learning applications using scikit-learn and PyTorch.Before you get started with this book, you'll need a good understanding of calculus, as well as linear algebra.Table of ContentsGiving Computers the Ability to Learn from DataTraining Simple Machine Learning Algorithms for ClassificationA Tour of Machine Learning Classifiers Using Scikit-LearnBuilding Good Training Datasets - Data PreprocessingCompressing Data via Dimensionality ReductionLearning Best Practices for Model Evaluation and Hyperparameter TuningCombining Different Models for Ensemble LearningApplying Machine Learning to Sentiment AnalysisPredicting Continuous Target Variables with Regression AnalysisWorking with Unlabeled Data - Clustering AnalysisImplementing a Multilayer Artificial Neural Network from Scratch(N.B. Please use the Look Inside option to see further chapters).
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Add to basketBuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Packed with clear explanations, visualizations, and working examples, the book covers essential machine learning techniques in depth, along with two cutting-edge machine learning techniques: transformers and graph neural networks.
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