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Condizione: As New. Unread book in perfect condition.
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EUR 63,88
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Aggiungi al carrelloBrand new book. Fast ship. Please provide full street address as we are not able to ship to P O box address.
Condizione: New.
Lingua: Inglese
Editore: Springer Nature Switzerland AG, Cham, 2020
ISBN 10: 3030185478 ISBN 13: 9783030185473
Da: Grand Eagle Retail, Bensenville, IL, U.S.A.
Paperback. Condizione: new. Paperback. This book, fully updated for Python version 3.6+, covers the key ideas that link probability, statistics, and machine learning illustrated using Python modules in these areas. All the figures and numerical results are reproducible using the Python codes provided. The author develops key intuitions in machine learning by working meaningful examples using multiple analytical methods and Python codes, thereby connecting theoretical concepts to concrete implementations. Detailed proofs for certain important results are also provided. Modern Python modules like Pandas, Sympy, Scikit-learn, Tensorflow, and Keras are applied to simulate and visualize important machine learning concepts like the bias/variance trade-off, cross-validation, and regularization. Many abstract mathematical ideas, such as convergence in probability theory, are developed and illustrated with numerical examples. This updated edition now includes the Fisher Exact Test and the Mann-Whitney-Wilcoxon Test. A new section on survival analysis has been included as well as substantial development of Generalized Linear Models. The new deep learning section for image processing includes an in-depth discussion of gradient descent methods that underpin all deep learning algorithms. As with the prior edition, there are new and updated *Programming Tips* that the illustrate effective Python modules and methods for scientific programming and machine learning. There are 445 run-able code blocks with corresponding outputs that have been tested for accuracy. Over 158 graphical visualizations (almost all generated using Python) illustrate the concepts that are developed both in code and in mathematics. We also discuss and use key Python modules such as Numpy, Scikit-learn, Sympy, Scipy, Lifelines, CvxPy, Theano, Matplotlib, Pandas, Tensorflow, Statsmodels, and Keras.This book is suitable for anyone with an undergraduate-level exposure to probability, statistics, or machine learning and with rudimentary knowledge of Python programming. This book, fully updated for Python version 3.6+, covers the key ideas that link probability, statistics, and machine learning illustrated using Python modules in these areas. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
EUR 60,72
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EUR 64,30
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EUR 31,95
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Aggiungi al carrelloHardcover. Condizione: Very Good. 1. Auflage. Unread, with a mimimum of shelfwear. Immediately dispatched from Germany.
EUR 62,59
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Da: SpringBooks, Berlin, Germania
EUR 32,95
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Aggiungi al carrelloHardcover. Condizione: Very Good. 2. Auflage. unread, cover with shelfwear or minor damages.
Lingua: Inglese
Editore: Springer Nature Switzerland AG, Cham, 2022
ISBN 10: 3030689549 ISBN 13: 9783030689544
Da: Grand Eagle Retail, Bensenville, IL, U.S.A.
Paperback. Condizione: new. Paperback. This textbook grew out of notes for the ECE143 Programming for Data Analysis class that the author has been teaching at University of California, San Diego, which is a requirement for both graduate and undergraduate degrees in Machine Learning and Data Science. This book is ideal for readers with some Python programming experience. The book covers key language concepts that must be understood to program effectively, especially for data analysis applications. Certain low-level language features are discussed in detail, especially Python memory management and data structures. Using Python effectively means taking advantage of its vast ecosystem. The book discusses Python package management and how to use third-party modules as well as how to structure your own Python modules. The section on object-oriented programming explains features of the language that facilitate common programming patterns.After developing the key Python language features, the book moves on to third-party modules that are foundational for effective data analysis, starting with Numpy. The book develops key Numpy concepts and discusses internal Numpy array data structures and memory usage. Then, the author moves onto Pandas and details its many features for data processing and alignment. Because strong visualizations are important for communicating data analysis, key modules such as Matplotlib are developed in detail, along with web-based options such as Bokeh, Holoviews, Altair, and Plotly.The text is sprinkled with many tricks-of-the-trade that help avoid common pitfalls. The author explains the internal logic embodied in the Python language so that readers can get into the Python mindset and make better design choices in their codes, which is especially helpful for newcomers to both Python and data analysis. To get the most out of this book, open a Python interpreter and type along with the many code samples. The author explains the internal logic embodied in the Python language so that readers can get into the Python mindset and make better design choices in their codes, which is especially helpful for newcomers to both Python and data analysis. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Condizione: As New. Unread book in perfect condition.
EUR 50,00
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Aggiungi al carrelloCondizione: very good. Gut/Very good: Buch bzw. Schutzumschlag mit wenigen Gebrauchsspuren an Einband, Schutzumschlag oder Seiten. / Describes a book or dust jacket that does show some signs of wear on either the binding, dust jacket or pages.
Condizione: New. pp. 528.
EUR 72,62
Quantità: 3 disponibili
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EUR 73,85
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EUR 74,48
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EUR 74,18
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Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
Da: Biblios, Frankfurt am main, HESSE, Germania
EUR 64,45
Quantità: 4 disponibili
Aggiungi al carrelloCondizione: New. pp. 528.
Lingua: Inglese
Editore: Springer International Publishing AG, Cham, 2023
ISBN 10: 3031046501 ISBN 13: 9783031046506
Da: Grand Eagle Retail, Bensenville, IL, U.S.A.
Paperback. Condizione: new. Paperback. Using a novel integration of mathematics and Python codes, this book illustrates the fundamental concepts that link probability, statistics, and machine learning, so that the reader can not only employ statistical and machine learning models using modern Python modules, but also understand their relative strengths and weaknesses. To clearly connect theoretical concepts to practical implementations, the author provides many worked-out examples along with "Programming Tips" that encourage the reader to write quality Python code. The entire text, including all the figures and numerical results, is reproducible using the Python codes provided, thus enabling readers to follow along by experimenting with the same code on their own computers. Modern Python modules like Pandas, Sympy, Scikit-learn, Statsmodels, Scipy, Xarray, Tensorflow, and Keras are used to implement and visualize important machine learning concepts like the bias/variance trade-off, cross-validation, interpretability, and regularization. Many abstract mathematical ideas, such as modes of convergence in probability, are explained and illustrated with concrete numerical examples. This book is suitable for anyone with undergraduate-level experience with probability, statistics, or machine learning and with rudimentary knowledge of Python programming. Using a novel integration of mathematics and Python codes, this book illustrates the fundamental concepts that link probability, statistics, and machine learning, so that the reader can not only employ statistical and machine learning models using modern Python modules, but also understand their relative strengths and weaknesses. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
EUR 60,05
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EUR 64,61
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Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 66,82
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Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 70,56
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Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 70,56
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