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Ajouter au panierPaperback or Softback. Etat : New. Hands-on Machine Learning with Python: Implement Neural Network Solutions with Scikit-learn and PyTorch. Book.
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Ajouter au panierTaschenbuch. Etat : Neu. Hands-on Machine Learning with Python | Implement Neural Network Solutions with Scikit-learn and PyTorch | Ashwin Pajankar (u. a.) | Taschenbuch | xx | Englisch | 2022 | Apress | EAN 9781484279205 | Verantwortliche Person für die EU: APress in Springer Science + Business Media, Heidelberger Platz 3, 14197 Berlin, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Langue: anglais
Edité par Springer, Berlin|Apress, 2022
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Ajouter au panierEtat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Here is the perfect comprehensive guide for readers with basic to intermediate level knowledge of machine learning and deep learning. It introduces tools such as NumPy for numerical processing, Pandas for panel data analysis, Matplotlib for visualization, S.
Langue: anglais
Edité par Apress, Apress Mär 2022, 2022
ISBN 10 : 1484279204 ISBN 13 : 9781484279205
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Ajouter au panierTaschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -Here is the perfect comprehensive guide for readers with basic to intermediate level knowledge of machine learning and deep learning. It introduces tools such as NumPy for numerical processing, Pandas for panel data analysis, Matplotlib for visualization, Scikit-learn for machine learning, and Pytorch for deep learning with Python. It also serves as a long-term reference manual for the practitioners who will find solutions to commonly occurring scenarios.Springer-Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 356 pp. Englisch.
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Ajouter au panierTaschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Here is the perfect comprehensive guide for readers with basic to intermediate level knowledge of machine learning and deep learning. It introduces tools such as NumPy for numerical processing, Pandas for panel data analysis, Matplotlib for visualization, Scikit-learn for machine learning, and Pytorch for deep learning with Python. It also serves as a long-term reference manual for the practitioners who will find solutions to commonly occurring scenarios.The book is divided into three sections. The first section introduces you to number crunching and data analysis tools using Python with in-depth explanation on environment configuration, data loading, numerical processing, data analysis, and visualizations. The second section covers machine learning basics and Scikit-learn library. It also explains supervised learning, unsupervised learning, implementation, and classification of regression algorithms, and ensemble learning methods in an easy manner with theoreticaland practical lessons. The third section explains complex neural network architectures with details on internal working and implementation of convolutional neural networks. The final chapter contains a detailed end-to-end solution with neural networks in Pytorch.After completing Hands-on Machine Learning with Python, you will be able to implement machine learning and neural network solutions and extend them to your advantage.What You'll LearnReview data structures in NumPy and PandasDemonstrate machine learning techniques and algorithmUnderstand supervised learning and unsupervised learningExamine convolutional neural networks and Recurrent neural networksGet acquainted with scikit-learn and PyTorchPredict sequences in recurrent neural networks and long short term memoryWho This Book Is ForData scientists, machine learning engineers, and software professionals with basic skills in Python programming.