Librería: Zoom Books East, Glendale Heights, IL, Estados Unidos de America
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Librería: World of Books (was SecondSale), Montgomery, IL, Estados Unidos de America
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
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Librería: Lakeside Books, Benton Harbor, MI, Estados Unidos de America
EUR 39,77
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Añadir al carritoCondición: New. Brand New! Not Overstocks or Low Quality Book Club Editions! Direct From the Publisher! We're not a giant, faceless warehouse organization! We're a small town bookstore that loves books and loves it's customers! Buy from Lakeside Books!
Idioma: Inglés
Publicado por O'Reilly Media 12/5/2023, 2023
ISBN 10: 1098146476 ISBN 13: 9781098146474
Librería: BargainBookStores, Grand Rapids, MI, Estados Unidos de America
EUR 44,05
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Añadir al carritoPaperback or Softback. Condición: New. Data Science: The Hard Parts: Techniques for Excelling at Data Science. Book.
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 42,19
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Añadir al carritoCondición: As New. Unread book in perfect condition.
EUR 45,18
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Añadir al carritoPAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.
EUR 42,89
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Añadir al carritoPAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.
Idioma: Inglés
Publicado por O'Reilly Media, Sebastopol, 2023
ISBN 10: 1098146476 ISBN 13: 9781098146474
Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de America
EUR 54,78
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Añadir al carritoPaperback. Condición: new. Paperback. This practical guide provides a collection of techniques and best practices that are generally overlooked in most data engineering and data science pedagogy. A common misconception is that great data scientists are experts in the "big themes" of the discipline-machine learning and programming. But most of the time, these tools can only take us so far. In practice, the smaller tools and skills really separate a great data scientist from a not-so-great one.Taken as a whole, the lessons in this book make the difference between an average data scientist candidate and a qualified data scientist working in the field. Author Daniel Vaughan has collected, extended, and used these skills to create value and train data scientists from different companies and industries.With this book, you will:Understand how data science creates valueDeliver compelling narratives to sell your data science projectBuild a business case using unit economics principlesCreate new features for a ML model using storytellingLearn how to decompose KPIsPerform growth decompositions to find root causes for changes in a metricDaniel Vaughan is head of data at Clip, the leading paytech company in Mexico. He's the author of Analytical Skills for AI and Data Science (O'Reilly). This practical guide provides a collection of techniques and best practices that are generally overlooked in most data engineering and data science pedagogy. Taken as a whole, the lessons in this book make the difference between an average data scientist candidate and a qualified data scientist working in the field. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
EUR 58,76
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Añadir al carritoPaperback. Condición: New. This practical guide provides a collection of techniques and best practices that are generally overlooked in most data engineering and data science pedagogy. A common misconception is that great data scientists are experts in the "big themes" of the discipline-machine learning and programming. But most of the time, these tools can only take us so far. In practice, the smaller tools and skills really separate a great data scientist from a not-so-great one.Taken as a whole, the lessons in this book make the difference between an average data scientist candidate and a qualified data scientist working in the field. Author Daniel Vaughan has collected, extended, and used these skills to create value and train data scientists from different companies and industries.With this book, you will:Understand how data science creates valueDeliver compelling narratives to sell your data science projectBuild a business case using unit economics principlesCreate new features for a ML model using storytellingLearn how to decompose KPIsPerform growth decompositions to find root causes for changes in a metricDaniel Vaughan is head of data at Clip, the leading paytech company in Mexico. He's the author of Analytical Skills for AI and Data Science (O'Reilly).
Librería: Brook Bookstore On Demand, Napoli, NA, Italia
EUR 47,12
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EUR 60,75
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Librería: GreatBookPricesUK, Woodford Green, Reino Unido
EUR 42,88
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Librería: Ria Christie Collections, Uxbridge, Reino Unido
EUR 50,18
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Idioma: Inglés
Publicado por O'Reilly Media 2023-11-17, 2023
ISBN 10: 1098146476 ISBN 13: 9781098146474
Librería: Chiron Media, Wallingford, Reino Unido
EUR 46,31
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Añadir al carritoPaperback. Condición: New.
Librería: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Irlanda
Original o primera edición
EUR 53,46
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Añadir al carritoCondición: New. 2023. 1st Edition. paperback. . . . . .
Librería: GreatBookPricesUK, Woodford Green, Reino Unido
EUR 48,97
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Añadir al carritoCondición: As New. Unread book in perfect condition.
Librería: THE SAINT BOOKSTORE, Southport, Reino Unido
EUR 52,38
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Añadir al carritoPaperback / softback. Condición: New. New copy - Usually dispatched within 4 working days.
Idioma: Inglés
Publicado por Oreilly & Associates Inc, 2023
ISBN 10: 1098146476 ISBN 13: 9781098146474
Librería: Revaluation Books, Exeter, Reino Unido
EUR 64,00
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Añadir al carritoPaperback. Condición: Brand New. 250 pages. 9.00x7.00x0.50 inches. In Stock.
EUR 67,27
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Añadir al carritoCondición: New. 2023. 1st Edition. paperback. . . . . . Books ship from the US and Ireland.
Librería: Majestic Books, Hounslow, Reino Unido
EUR 70,23
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Añadir al carritoCondición: New. pp. 248.
Librería: Books Puddle, New York, NY, Estados Unidos de America
EUR 85,27
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Añadir al carritoCondición: New. pp. 248 1st edition NO-PA16APR2015-KAP.
EUR 43,64
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Idioma: Inglés
Publicado por O'Reilly Media, Sebastopol, 2023
ISBN 10: 1098146476 ISBN 13: 9781098146474
Librería: AussieBookSeller, Truganina, VIC, Australia
EUR 82,95
Cantidad disponible: 1 disponibles
Añadir al carritoPaperback. Condición: new. Paperback. This practical guide provides a collection of techniques and best practices that are generally overlooked in most data engineering and data science pedagogy. A common misconception is that great data scientists are experts in the "big themes" of the discipline-machine learning and programming. But most of the time, these tools can only take us so far. In practice, the smaller tools and skills really separate a great data scientist from a not-so-great one.Taken as a whole, the lessons in this book make the difference between an average data scientist candidate and a qualified data scientist working in the field. Author Daniel Vaughan has collected, extended, and used these skills to create value and train data scientists from different companies and industries.With this book, you will:Understand how data science creates valueDeliver compelling narratives to sell your data science projectBuild a business case using unit economics principlesCreate new features for a ML model using storytellingLearn how to decompose KPIsPerform growth decompositions to find root causes for changes in a metricDaniel Vaughan is head of data at Clip, the leading paytech company in Mexico. He's the author of Analytical Skills for AI and Data Science (O'Reilly). This practical guide provides a collection of techniques and best practices that are generally overlooked in most data engineering and data science pedagogy. Taken as a whole, the lessons in this book make the difference between an average data scientist candidate and a qualified data scientist working in the field. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
EUR 54,76
Cantidad disponible: 15 disponibles
Añadir al carritoPaperback. Condición: New. This practical guide provides a collection of techniques and best practices that are generally overlooked in most data engineering and data science pedagogy. A common misconception is that great data scientists are experts in the "big themes" of the discipline-machine learning and programming. But most of the time, these tools can only take us so far. In practice, the smaller tools and skills really separate a great data scientist from a not-so-great one.Taken as a whole, the lessons in this book make the difference between an average data scientist candidate and a qualified data scientist working in the field. Author Daniel Vaughan has collected, extended, and used these skills to create value and train data scientists from different companies and industries.With this book, you will:Understand how data science creates valueDeliver compelling narratives to sell your data science projectBuild a business case using unit economics principlesCreate new features for a ML model using storytellingLearn how to decompose KPIsPerform growth decompositions to find root causes for changes in a metricDaniel Vaughan is head of data at Clip, the leading paytech company in Mexico. He's the author of Analytical Skills for AI and Data Science (O'Reilly).
Idioma: Inglés
Publicado por O'reilly Media Dez 2023, 2023
ISBN 10: 1098146476 ISBN 13: 9781098146474
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 67,03
Cantidad disponible: 2 disponibles
Añadir al carritoTaschenbuch. Condición: Neu. Neuware - This practical guide provides a collection of techniques and best practices that are generally overlooked in most data engineering and data science pedagogy. A common misconception is that great data scientists are experts in the 'big themes' of the discipline--machine learning and programming. But most of the time, these tools can only take us so far. In practice, the smaller tools and skills really separate a great data scientist from a not-so-great one.
Librería: Buchpark, Trebbin, Alemania
EUR 27,34
Cantidad disponible: 2 disponibles
Añadir al carritoCondición: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | This practical guide provides a collection of techniques and best practices that are generally overlooked in most data engineering and data science pedagogy. A common misconception is that great data scientists are experts in the "big themes" of the discipline--machine learning and programming. But most of the time, these tools can only take us so far. In practice, the smaller tools and skills really separate a great data scientist from a not-so-great one. Taken as a whole, the lessons in this book make the difference between an average data scientist candidate and a qualified data scientist working in the field. Author Daniel Vaughan has collected, extended, and used these skills to create value and train data scientists from different companies and industries. With this book, you will: - Understand how data science creates value - Deliver compelling narratives to sell your data science project - Build a business case using unit economics principles - Create new features for a ML model using storytelling - Learn how to decompose KPIs - Perform growth decompositions to find root causes for changes in a metric Daniel Vaughan is head of data at Clip, the leading paytech company in Mexico. He's the author of Analytical Skills for AI and Data Science (O'Reilly).
Idioma: Inglés
Publicado por Oreilly & Associates Inc, 2023
ISBN 10: 1098146476 ISBN 13: 9781098146474
Librería: Revaluation Books, Exeter, Reino Unido
EUR 59,78
Cantidad disponible: 2 disponibles
Añadir al carritoPaperback. Condición: Brand New. 250 pages. 9.00x7.00x0.50 inches. In Stock. This item is printed on demand.