Da: Goodwill Books, Hillsboro, OR, U.S.A.
Condizione: acceptable. Fairly worn, but readable and intact. If applicable: Dust jacket, disc or access code may not be included.
Da: books4less (Versandantiquariat Petra Gros GmbH & Co. KG), Welling, Germania
EUR 3,95
Quantità: 1 disponibili
Aggiungi al carrelloBroschiert. Condizione: Gut. 124 Seiten; Das Buch befindet sich in einem gut erhaltenen Zustand. Neben dem oben aufgeführten Aufsatz befinden sich auch weitere Beiträge auch anderer Autoren in dem Werk. Sprache: Deutsch Gewicht in Gramm: 385.
Da: Coffee Cat Books, Chapel Hill, NC, U.S.A.
paperback. Condizione: VERY GOOD. Very Good. Unmarked. Clean, unmarked interior. Softcover, clean & bright, some edge corner and shelf wear. No rips, chips, stains or tears. Binding solid. 2017 Edition (4th release 2018). hips from USA, quickly and with care. Introduction to Machine Learning with Python: A Guide for Data Scientists by Andreas C. Müller and Sarah Guido provides practical guidance on implementing machine learning solutions using Python and the scikit-learn library, focusing on real-world applications over theoretical concepts.
Da: Meadowland Media, Fayetteville, AR, U.S.A.
paperback. it'S NEW Ships same or next bu.
Condizione: good. A copy that has been read, remains in good condition. All pages are intact, and the cover is intact. The spine and cover show signs of wear. Pages can include notes and highlighting and show signs of wear, and the copy can include "From the library of" labels or previous owner inscriptions. 100% GUARANTEE! Shipped with delivery confirmation, if you're not satisfied with purchase please return item for full refund. Ships via media mail.
Da: GreatBookPrices, Columbia, MD, U.S.A.
Condizione: New.
Da: GreatBookPrices, Columbia, MD, U.S.A.
Condizione: As New. Unread book in perfect condition.
Condizione: New.
Da: PBShop.store US, Wood Dale, IL, U.S.A.
PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.
Da: PBShop.store UK, Fairford, GLOS, Regno Unito
EUR 38,62
Quantità: 15 disponibili
Aggiungi al carrelloPAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.
Condizione: New.
Condizione: As New. Unread book in perfect condition.
Condizione: As New. Unread book in perfect condition.
Da: Brook Bookstore On Demand, Napoli, NA, Italia
EUR 42,97
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: new.
Lingua: Inglese
Editore: O'Reilly Media, Sebastopol, 2016
ISBN 10: 1449369413 ISBN 13: 9781449369415
Da: Grand Eagle Retail, Bensenville, IL, U.S.A.
Paperback. Condizione: new. Paperback. Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions. With all the data available today, machine learning applications are limited only by your imagination.Youll learn the steps necessary to create a successful machine-learning application with Python and the scikit-learn library. Authors Andreas Mller and Sarah Guido focus on the practical aspects of using machine learning algorithms, rather than the math behind them. Familiarity with the NumPy and matplotlib libraries will help you get even more from this book.With this book, youll learn:Fundamental concepts and applications of machine learningAdvantages and shortcomings of widely used machine learning algorithmsHow to represent data processed by machine learning, including which data aspects to focus onAdvanced methods for model evaluation and parameter tuningThe concept of pipelines for chaining models and encapsulating your workflowMethods for working with text data, including text-specific processing techniquesSuggestions for improving your machine learning and data science skillsAbout the AuthorsSarah is a data scientist at Reonomy, where she's helping to build disruptive tech in the commercial real estate industry in New York City. Three of her favorite things are Python, data, and machine learning. Andreas Mueller received his PhD in machine learning from the University of Bonn. After working as a machine learning researcher on computer vision applications at Amazon for a year, he joined the Center for Data Science at the New York University, and later the Columbia University Data Science Institute. In the last four years, he has been maintainer and one of the core contributor of scikit-learn, a machine learning toolkit widely used in industry and academia, and author and contributor to several other widely used machine learning packages. His mission is to create open tools to lower the barrier of entry for machine learning applications, promote reproducible science and democratize the access to high-quality machine learning algorithms. Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Lingua: Tedesco
Editore: Wellhofer Verlag 2016-03-09, 2016
ISBN 10: 3954281864 ISBN 13: 9783954281862
Da: Chiron Media, Wallingford, Regno Unito
EUR 12,51
Quantità: 3 disponibili
Aggiungi al carrelloPaperback. Condizione: New.
Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 35,42
Quantità: 10 disponibili
Aggiungi al carrelloCondizione: New.
Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 38,53
Quantità: 10 disponibili
Aggiungi al carrelloCondizione: New.
Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 38,92
Quantità: 10 disponibili
Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
Condizione: New.
Da: Rarewaves.com USA, London, LONDO, Regno Unito
EUR 58,08
Quantità: 8 disponibili
Aggiungi al carrelloPaperback. Condizione: New. Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions. With all the data available today, machine learning applications are limited only by your imagination. You'll learn the steps necessary to create a successful machine-learning application with Python and the scikit-learn library. Authors Andreas Muller and Sarah Guido focus on the practical aspects of using machine learning algorithms, rather than the math behind them. Familiarity with the NumPy and matplotlib libraries will help you get even more from this book.With this book, you'll learn: Fundamental concepts and applications of machine learning Advantages and shortcomings of widely used machine learning algorithms How to represent data processed by machine learning, including which data aspects to focus on Advanced methods for model evaluation and parameter tuning The concept of pipelines for chaining models and encapsulating your workflow Methods for working with text data, including text-specific processing techniques Suggestions for improving your machine learning and data science skills.
Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 44,10
Quantità: 16 disponibili
Aggiungi al carrelloCondizione: New. In.
Da: Majestic Books, Hounslow, Regno Unito
EUR 52,38
Quantità: 3 disponibili
Aggiungi al carrelloCondizione: New. 400.
Da: Rarewaves USA, OSWEGO, IL, U.S.A.
EUR 61,24
Quantità: Più di 20 disponibili
Aggiungi al carrelloPaperback. Condizione: New. Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions. With all the data available today, machine learning applications are limited only by your imagination. You'll learn the steps necessary to create a successful machine-learning application with Python and the scikit-learn library. Authors Andreas Muller and Sarah Guido focus on the practical aspects of using machine learning algorithms, rather than the math behind them. Familiarity with the NumPy and matplotlib libraries will help you get even more from this book.With this book, you'll learn: Fundamental concepts and applications of machine learning Advantages and shortcomings of widely used machine learning algorithms How to represent data processed by machine learning, including which data aspects to focus on Advanced methods for model evaluation and parameter tuning The concept of pipelines for chaining models and encapsulating your workflow Methods for working with text data, including text-specific processing techniques Suggestions for improving your machine learning and data science skills.
Da: California Books, Miami, FL, U.S.A.
EUR 61,46
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New.
Soft cover. Condizione: New. BRAND NEW softcover. Book.
Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 45,53
Quantità: 10 disponibili
Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
Da: Books Puddle, New York, NY, U.S.A.
Condizione: New. 400.
EUR 35,00
Quantità: 1 disponibili
Aggiungi al carrelloCondizione: Neuf.
Da: Biblios, Frankfurt am main, HESSE, Germania
EUR 61,72
Quantità: 3 disponibili
Aggiungi al carrelloCondizione: New. 400.