ISBN 10: 1484283902 ISBN 13: 9781484283905
Librería: Romtrade Corp., STERLING HEIGHTS, MI, Estados Unidos de America
EUR 29,10
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Añadir al carritoCondición: New. Brand New. Soft Cover International Edition. Different ISBN and Cover Image. Priced lower than the standard editions which is usually intended to make them more affordable for students abroad. The core content of the book is generally the same as the standard edition. The country selling restrictions may be printed on the book but is no problem for the self-use. This Item maybe shipped from US or any other country as we have multiple locations worldwide.
Librería: BargainBookStores, Grand Rapids, MI, Estados Unidos de America
EUR 42,24
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Añadir al carritoPaperback or Softback. Condición: New. Hands-on Machine Learning with Python: Implement Neural Network Solutions with Scikit-learn and PyTorch 1.36. Book.
Librería: California Books, Miami, FL, Estados Unidos de America
EUR 47,57
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 39,90
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 41,87
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Añadir al carritoCondición: As New. Unread book in perfect condition.
Librería: Rarewaves USA, OSWEGO, IL, Estados Unidos de America
Original o primera edición
EUR 56,59
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Añadir al carritoPaperback. Condición: New. 1st ed. 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 Pandas Demonstrate machine learning techniques and algorithmUnderstand supervised learning and unsupervised learning Examine convolutional neural networks and Recurrent neural networksGet acquainted with scikit-learn and PyTorchPredict sequences in recurrent neural networks and long short term memory Who This Book Is ForData scientists, machine learning engineers, and software professionals with basic skills in Python programming.
Librería: Rarewaves USA United, OSWEGO, IL, Estados Unidos de America
Original o primera edición
EUR 58,11
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Añadir al carritoPaperback. Condición: New. 1st ed. 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 Pandas Demonstrate machine learning techniques and algorithmUnderstand supervised learning and unsupervised learning Examine convolutional neural networks and Recurrent neural networksGet acquainted with scikit-learn and PyTorchPredict sequences in recurrent neural networks and long short term memory Who This Book Is ForData scientists, machine learning engineers, and software professionals with basic skills in Python programming.
Librería: Rarewaves.com UK, London, Reino Unido
Original o primera edición
EUR 60,98
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Añadir al carritoPaperback. Condición: New. 1st ed. 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 Pandas Demonstrate machine learning techniques and algorithmUnderstand supervised learning and unsupervised learning Examine convolutional neural networks and Recurrent neural networksGet acquainted with scikit-learn and PyTorchPredict sequences in recurrent neural networks and long short term memory Who This Book Is ForData scientists, machine learning engineers, and software professionals with basic skills in Python programming.
Librería: Majestic Books, Hounslow, Reino Unido
EUR 54,53
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Librería: Books Puddle, New York, NY, Estados Unidos de America
EUR 55,40
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Añadir al carritoCondición: New. 1st ed. edition NO-PA16APR2015-KAP.
Librería: GreatBookPricesUK, Woodford Green, Reino Unido
EUR 50,54
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Librería: Rarewaves.com USA, London, LONDO, Reino Unido
Original o primera edición
EUR 68,29
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Añadir al carritoPaperback. Condición: New. 1st ed. 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 Pandas Demonstrate machine learning techniques and algorithmUnderstand supervised learning and unsupervised learning Examine convolutional neural networks and Recurrent neural networksGet acquainted with scikit-learn and PyTorchPredict sequences in recurrent neural networks and long short term memory Who This Book Is ForData scientists, machine learning engineers, and software professionals with basic skills in Python programming.
Librería: GreatBookPricesUK, Woodford Green, Reino Unido
EUR 53,73
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Librería: Ria Christie Collections, Uxbridge, Reino Unido
EUR 66,75
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Librería: Biblios, Frankfurt am main, HESSE, Alemania
EUR 57,10
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ISBN 10: 1484283902 ISBN 13: 9781484283905
Librería: Basi6 International, Irving, TX, Estados Unidos de America
EUR 29,10
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Añadir al carritoCondición: Brand New. New.SoftCover International edition. Different ISBN and Cover image but contents are same as US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.
Librería: Lucky's Textbooks, Dallas, TX, Estados Unidos de America
EUR 42,23
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Publicado por Springer, Berlin|Apress, 2022
ISBN 10: 1484279204 ISBN 13: 9781484279205
Idioma: Inglés
Librería: moluna, Greven, Alemania
EUR 52,37
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Añadir al carritoKartoniert / Broschiert. Condición: 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.