Underwood todd (28 Ergebnisse)

Paperback. Zustand: Very Good. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting. Todd, Sue; Underwood, Emily (illustrator).

Paperback. Zustand: Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less. Todd, Sue; Underwood, Emily (illustrator).

Paperback. Zustand: New. Todd, Sue; Underwood, Emily (illustrator).

Zustand: New.

Paperback. Zustand: Very Good. no jacket (paperback). First Edition. This paperback edition of Reliable Machine Learning is in excellent condition, with no visible signs of wear or damage. The cover and pages are intact and clean, and there are no inscriptions or library markings. The book does not include a dust jacket, as it is a paperback. Kate Dullea (illustrator).…

Zustand: New. Todd, Sue; Underwood, Emily (illustrator).

Zustand: New.

Paperback. Zustand: Brand New. 44 pages. 10.00x8.00x0.11 inches. In Stock. Todd, Sue; Underwood, Emily (illustrator).

Zustand: New.

Zustand: New. Todd, Sue; Underwood, Emily (illustrator).

Zustand: As New. Unread book in perfect condition. Todd, Sue; Underwood, Emily (illustrator).

Paperback. Zustand: New. Whether you're part of a small startup or a planet-spanning megacorp, this practical book shows data scientists, SREs, and business owners how to run ML reliably, effectively, and accountably within your organization. You'll gain insight into everything from how to do model monitoring in production to how to run a well-tuned model development team in a product organization.By applying an SRE mindset to machine learning, authors and engineering professionals Cathy Chen, Kranti Parisa, Niall Richard Murphy, D. Sculley, Todd Underwood, and featured guests show you how to run an efficient ML system. Whether you want to increase revenue, optimize decision-making, solve problems, or understand and influence customer behavior, you'll learn how to perform day-to-day ML tasks while keeping the bigger picture in mind.You'll examine:What ML is: how it functions and what it relies onConceptual frameworks for understanding how ML "loops" workEffective "productionization," and how it can be made easily monitorable, deployable, and operableWhy ML systems make production troubleshooting more difficult, and how to get around themHow ML, product, and production teams can communicate effectively.…

Paperback. Zustand: New. Brand new book, sourced directly from publisher. Dispatch time is 24-48 hours from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely.

Zustand: New.

Paperback. Zustand: New. This anthology features forty talented writers from Arkansas, Oklahoma, Texas, Louisiana, and other surrounding states that represent a unique part of American culture. While this region is often misunderstood as one type of place, the Mid-South belongs to a little bit of everywhere: part Southwest, part Midwest, part South-always wild. Our area of the country is both a space of its own and part of a larger, complicated Southern world: the "Mid/South." In this collection, poetry, short stories, and essays offer glimpses into this in-between place as they explore the complexities of our relationships to each other as well as to the natural world. Whether through vivid landscapes, family dramas, or bittersweet love stories, each piece brings more insight into what it means to be from around here.…

Paperback. Zustand: New. Whether you're part of a small startup or a planet-spanning megacorp, this practical book shows data scientists, SREs, and business owners how to run ML reliably, effectively, and accountably within your organization. You'll gain insight into everything from how to do model monitoring in production to how to run a well-tuned model development team in a product organization.By applying an SRE mindset to machine learning, authors and engineering professionals Cathy Chen, Kranti Parisa, Niall Richard Murphy, D. Sculley, Todd Underwood, and featured guests show you how to run an efficient ML system. Whether you want to increase revenue, optimize decision-making, solve problems, or understand and influence customer behavior, you'll learn how to perform day-to-day ML tasks while keeping the bigger picture in mind.You'll examine:What ML is: how it functions and what it relies onConceptual frameworks for understanding how ML "loops" workEffective "productionization," and how it can be made easily monitorable, deployable, and operableWhy ML systems make production troubleshooting more difficult, and how to get around themHow ML, product, and production teams can communicate effectively.…

Zustand: New.

Zustand: New. In English.

Zustand: New.

Zustand: As New. Unread book in perfect condition.

Zustand: New.

Paperback. Zustand: New. Todd, Sue; Underwood, Emily (illustrator).

Paperback. Zustand: Brand New. 350 pages. 9.19x7.00x1.00 inches. In Stock.

Zustand: NEW.

Paperback. Zustand: New. Whether you're part of a small startup or a planet-spanning megacorp, this practical book shows data scientists, SREs, and business owners how to run ML reliably, effectively, and accountably within your organization. You'll gain insight into everything from how to do model monitoring in production to how to run a well-tuned model development team in a product organization.By applying an SRE mindset to machine learning, authors and engineering professionals Cathy Chen, Kranti Parisa, Niall Richard Murphy, D. Sculley, Todd Underwood, and featured guests show you how to run an efficient ML system. Whether you want to increase revenue, optimize decision-making, solve problems, or understand and influence customer behavior, you'll learn how to perform day-to-day ML tasks while keeping the bigger picture in mind.You'll examine:What ML is: how it functions and what it relies onConceptual frameworks for understanding how ML "loops" workEffective "productionization," and how it can be made easily monitorable, deployable, and operableWhy ML systems make production troubleshooting more difficult, and how to get around themHow ML, product, and production teams can communicate effectively.…

Zustand: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | Who needs a forest fire? We do! But not the kind we have now.The first people who lived in California did not fight fire. They used it as a tool and tended the forest floor like a garden for thousands of years. The California Gold Rush of 1849 brought settlers and miners who killed Native Americans and destroyed forest ecosystems. Stopping all fires and allowing the forest floor to become overcrowded and overgrown led to conditions that were perfect for major wildfires: megafires!This book will help you:-Learn why plants and animals need fire-Understand how the Native American people of California used fire as a tool to keep the forest ecology strong-Discover what we can do to help forests and California's native plants and animals avoid megafires.Extensive educational resources in the back matter align with California state educational standards. A FREE Teacher's Guide is available with activities, games, additional resources and more. Todd, Sue; Underwood, Emily (illustrator). …

Zustand: New. &Uumlber den AutorCathy Chen, CPCC, MA specializes in coaching tech leaders enabling development of their own skills in leading teams. She has held the role of technical program manager, product manager, and engineering manager. She has.

Paperback. Zustand: New. Whether you're part of a small startup or a planet-spanning megacorp, this practical book shows data scientists, SREs, and business owners how to run ML reliably, effectively, and accountably within your organization. You'll gain insight into everything from how to do model monitoring in production to how to run a well-tuned model development team in a product organization.By applying an SRE mindset to machine learning, authors and engineering professionals Cathy Chen, Kranti Parisa, Niall Richard Murphy, D. Sculley, Todd Underwood, and featured guests show you how to run an efficient ML system. Whether you want to increase revenue, optimize decision-making, solve problems, or understand and influence customer behavior, you'll learn how to perform day-to-day ML tasks while keeping the bigger picture in mind.You'll examine:What ML is: how it functions and what it relies onConceptual frameworks for understanding how ML "loops" workEffective "productionization," and how it can be made easily monitorable, deployable, and operableWhy ML systems make production troubleshooting more difficult, and how to get around themHow ML, product, and production teams can communicate effectively.…