Applied Data Science Using by Kakarla Ramcharan (19 results)
Applied Data Science Using PySpark: Learn the End-to-End Predictive Model-Building Cycle
Kakarla, Ramcharan,Krishnan, Sundar,Dhamodharan, Balaji,Gunnu, Venkata
Published by Apress, 2024
- Softcover
Seller: Books From California, Simi Valley, CA, U.S.A.Books From California
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Paperback. Condition: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority.
Applied Data Science Using Pyspark : Learn the End-to-end Predictive Model-building Cycle
Kakarla, Ramcharan; Krishnan, Sundar; Dhamodharan, Balaji; Gunnu, Venkata
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Applied Data Science Using Pyspark : Learn the End-to-end Predictive Model-building Cycle
Kakarla, Ramcharan; Krishnan, Sundar; Dhamodharan, Balaji; Gunnu, Venkata
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Applied Data Science Using PySpark: Learn the End-to-End Predictive Model-Building Cycle
Kakarla, Ramcharan; Krishnan, Sundar; Dhamodharan, Balaji; Gunnu, Venkata
- Softcover
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paperback. Condition: Very Good. Applied Data Science Using PySpark: Learn the End-to-End Predictive Model-Building Cycle This book is in very good condition and will be shipped within 24 hours of ordering. The cover may have some limited signs of wear but the pages are clean, intact and the spine remains undamaged. This book ha…s clearly been well maintained and looked after thus far. Money back guarantee if you are not satisfied. See all our books here, order more than 1 book and get discounted shipping. .
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paperback. Condition: Very Good. Shipped within 24 hours from our UK warehouse. Clean, undamaged book with no damage to pages and minimal wear to the cover. Spine still tight, in very good condition. Remember if you are not happy, you are covered by our 100% money back guarantee.
Applied Data Science Using Pyspark : Learn the End-to-end Predictive Model-building Cycle
Kakarla, Ramcharan; Krishnan, Sundar; Dhamodharan, Balaji; Gunnu, Venkata
- Softcover
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Applied Data Science Using Pyspark : Learn the End-to-end Predictive Model-building Cycle
Kakarla, Ramcharan; Krishnan, Sundar; Dhamodharan, Balaji; Gunnu, Venkata
- Softcover
Seller: GreatBookPricesUK, Woodford Green, United KingdomGreatBookPricesUK
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Applied Data Science Using PySpark
Kakarla, Ramcharan; Krishnan, Sundar; Dhamodharan, Balaji; Gunnu, Venkata
- Softcover
Seller: PBShop.store UK, Fairford, GLOS, United KingdomPBShop.store UK
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Applied Data Science Using PySpark
Ramcharan Kakarla, Sundar Krishnan, Balaji Dhamodharan, Venkata Gunnu
- Softcover
Seller: Rarewaves.com USA, London, LONDO, United KingdomRarewaves.com USA
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Paperback. Condition: New. Second Edition. This comprehensive guide, featuring hand-picked examples of daily use cases, will walk you through the end-to-end predictive model-building cycle using the latest techniques and industry tricks. In Chapters 1, 2, and 3, we will begin by setting up the environment and covering the basics… of PySpark, focusing on data manipulation. Chapter 4 delves into the art of variable selection, demonstrating various techniques available in PySpark. In Chapters 5, 6, and 7, we explore machine learning algorithms, their implementations, and fine-tuning techniques. Chapters 8 and 9 will guide you through machine learning pipelines and various methods to operationalize and serve models using Docker/API. Chapter 10 will demonstrate how to unlock the power of predictive models to create a meaningful impact on your business. Chapter 11 introduces some of the most widely used and powerful modeling frameworks to unlock real value from data. In this new edition, you will learn predictive modeling frameworks that can quantify customer lifetime values and estimate the return on your predictive modeling investments. This edition also includes methods to measure engagement and identify actionable populations for effective churn treatments. Additionally, a dedicated chapter on experimentation design has been added, covering steps to efficiently design, conduct, test, and measure the results of your models. All code examples have been updated to reflect the latest stable version of Spark. You will:Gain an overview of end-to-end predictive model buildingUnderstand multiple variable selection techniques and their implementationsLearn how to operationalize modelsPerform data science experiments and learn useful tips.
Applied Data Science Using PySpark: Learn the End-to-End Predictive Model-Building Cycle
Kakarla, Ramcharan; Krishnan, Sundar; Dhamodharan, Balaji; Gunnu, Venkata
- Softcover
Seller: Ria Christie Collections, Uxbridge, United KingdomRia Christie Collections
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Applied Data Science Using PySpark
Ramcharan Kakarla, Sundar Krishnan, Balaji Dhamodharan, Venkata Gunnu
- Softcover
Seller: Rarewaves.com UK, London, United KingdomRarewaves.com UK
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Paperback. Condition: New. Second Edition. This comprehensive guide, featuring hand-picked examples of daily use cases, will walk you through the end-to-end predictive model-building cycle using the latest techniques and industry tricks. In Chapters 1, 2, and 3, we will begin by setting up the environment and covering the basics… of PySpark, focusing on data manipulation. Chapter 4 delves into the art of variable selection, demonstrating various techniques available in PySpark. In Chapters 5, 6, and 7, we explore machine learning algorithms, their implementations, and fine-tuning techniques. Chapters 8 and 9 will guide you through machine learning pipelines and various methods to operationalize and serve models using Docker/API. Chapter 10 will demonstrate how to unlock the power of predictive models to create a meaningful impact on your business. Chapter 11 introduces some of the most widely used and powerful modeling frameworks to unlock real value from data. In this new edition, you will learn predictive modeling frameworks that can quantify customer lifetime values and estimate the return on your predictive modeling investments. This edition also includes methods to measure engagement and identify actionable populations for effective churn treatments. Additionally, a dedicated chapter on experimentation design has been added, covering steps to efficiently design, conduct, test, and measure the results of your models. All code examples have been updated to reflect the latest stable version of Spark. You will:Gain an overview of end-to-end predictive model buildingUnderstand multiple variable selection techniques and their implementationsLearn how to operationalize modelsPerform data science experiments and learn useful tips.
- Softcover
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Seller: Brook Bookstore On Demand, Napoli, NA, ItalyBrook Bookstore On Demand
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Condition: new. Questo è un articolo print on demand.
- Softcover
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Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermanyBuchWeltWeit Ludwig Meier e.K.
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This comprehensive guide, featuring hand-picked examples of daily use cases, will walk you through the end-to-end predictive model-building cycle using the latest techniques and industry tricks. In Chapters 1, 2, and 3, we will begi…n by setting up the environment and covering the basics of PySpark, focusing on data manipulation. Chapter 4 delves into the art of variable selection, demonstrating various techniques available in PySpark. In Chapters 5, 6, and 7, we explore machine learning algorithms, their implementations, and fine-tuning techniques. Chapters 8 and 9 will guide you through machine learning pipelines and various methods to operationalize and serve models using Docker/API. Chapter 10 will demonstrate how to unlock the power of predictive models to create a meaningful impact on your business. Chapter 11 introduces some of the most widely used and powerful modeling frameworks to unlock real value from data.In this new edition, you will learn predictive modeling frameworks that can quantify customer lifetime values and estimate the return on your predictive modeling investments. This edition also includes methods to measure engagement and identify actionable populations for effective churn treatments. Additionally, a dedicated chapter on experimentation design has been added, covering steps to efficiently design, conduct, test, and measure the results of your models. All code examples have been updated to reflect the latest stable version of Spark.You will:Gain an overview of end-to-end predictive model buildingUnderstand multiple variable selection techniques and their implementationsLearn how to operationalize modelsPerform data science experiments and learn useful tips 468 pp. Englisch.
Applied Data Science Using PySpark
Kakarla, Ramcharan; Krishnan, Sundar; Dhamodharan, Balaji; Gunnu, Venkata
- Softcover
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Seller: moluna, Greven, Germanymoluna
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt.
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Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germanybuchversandmimpf2000
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This comprehensive guide, featuring hand-picked examples of daily use cases, will walk you through the end-to-end predictive model-building cycle using the latest techniques and industry tricks. In Chapters 1, 2, and 3, we will begin by… setting up the environment and covering the basics of PySpark, focusing on data manipulation. Chapter 4 delves into the art of variable selection, demonstrating various techniques available in PySpark. In Chapters 5, 6, and 7, we explore machine learning algorithms, their implementations, and fine-tuning techniques. Chapters 8 and 9 will guide you through machine learning pipelines and various methods to operationalize and serve models using Docker/API. Chapter 10 will demonstrate how to unlock the power of predictive models to create a meaningful impact on your business. Chapter 11 introduces some of the most widely used and powerful modeling frameworks to unlock real value from data.In this new edition, you will learn predictive modeling frameworks that can quantify customer lifetime values and estimate the return on your predictive modeling investments. This edition also includes methods to measure engagement and identify actionable populations for effective churn treatments. Additionally, a dedicated chapter on experimentation design has been added, covering steps to efficiently design, conduct, test, and measure the results of your models. All code examples have been updated to reflect the latest stable version of Spark.You will:Gain an overview of end-to-end predictive model buildingUnderstand multiple variable selection techniques and their implementationsLearn how to operationalize modelsPerform data science experiments and learn useful tipsSpringer-Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 468 pp. Englisch.
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Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This comprehensive guide, featuring hand-picked examples of daily use cases, will walk you through the end-to-end predictive model-building cycle using the latest techniques and industry tricks. In Chapters 1, 2, and 3, we will begin by…setting up the environment and covering the basics of PySpark, focusing on data manipulation. Chapter 4 delves into the art of variable selection, demonstrating various techniques available in PySpark. In Chapters 5, 6, and 7, we explore machine learning algorithms, their implementations, and fine-tuning techniques. Chapters 8 and 9 will guide you through machine learning pipelines and various methods to operationalize and serve models using Docker/API. Chapter 10 will demonstrate how to unlock the power of predictive models to create a meaningful impact on your business. Chapter 11 introduces some of the most widely used and powerful modeling frameworks to unlock real value from data.In this new edition, you will learn predictive modeling frameworks that can quantify customer lifetime values and estimate the return on your predictive modeling investments. This edition also includes methods to measure engagement and identify actionable populations for effective churn treatments. Additionally, a dedicated chapter on experimentation design has been added, covering steps to efficiently design, conduct, test, and measure the results of your models. All code examples have been updated to reflect the latest stable version of Spark.You will:Gain an overview of end-to-end predictive model buildingUnderstand multiple variable selection techniques and their implementationsLearn how to operationalize modelsPerform data science experiments and learn useful tips.
