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Managing Data Science: Effective strategies to manage data science projects and build a sustainable team
Paperback

Managing Data Science: Effective strategies to manage data science projects and build a sustainable team

$78.99
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This title is printed to order. This book may have been self-published. If so, we cannot guarantee the quality of the content. In the main most books will have gone through the editing process however some may not. We therefore suggest that you be aware of this before ordering this book. If in doubt check either the author or publisher’s details as we are unable to accept any returns unless they are faulty. Please contact us if you have any questions.

Understand data science concepts and methodologies to manage and deliver top-notch solutions for your organization

Key Features

Learn the basics of data science and explore its possibilities and limitations Manage data science projects and assemble teams effectively even in the most challenging situations Understand management principles and approaches for data science projects to streamline the innovation process

Book DescriptionData science and machine learning can transform any organization and unlock new opportunities. However, employing the right management strategies is crucial to guide the solution from prototype to production. Traditional approaches often fail as they don’t entirely meet the conditions and requirements necessary for current data science projects. In this book, you’ll explore the right approach to data science project management, along with useful tips and best practices to guide you along the way.

After understanding the practical applications of data science and artificial intelligence, you’ll see how to incorporate them into your solutions. Next, you will go through the data science project life cycle, explore the common pitfalls encountered at each step, and learn how to avoid them. Any data science project requires a skilled team, and this book will offer the right advice for hiring and growing a data science team for your organization. Later, you’ll be shown how to efficiently manage and improve your data science projects through the use of DevOps and ModelOps.

By the end of this book, you will be well versed with various data science solutions and have gained practical insights into tackling the different challenges that you’ll encounter on a daily basis.

What you will learn

Understand the underlying problems of building a strong data science pipeline Explore the different tools for building and deploying data science solutions Hire, grow, and sustain a data science team Manage data science projects through all stages, from prototype to production Learn how to use ModelOps to improve your data science pipelines Get up to speed with the model testing techniques used in both development and production stages

Who this book is forThis book is for data scientists, analysts, and program managers who want to use data science for business productivity by incorporating data science workflows efficiently. Some understanding of basic data science concepts will be useful to get the most out of this book.

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MORE INFO
Format
Paperback
Publisher
Packt Publishing Limited
Country
United Kingdom
Date
12 November 2019
Pages
290
ISBN
9781838826321

This title is printed to order. This book may have been self-published. If so, we cannot guarantee the quality of the content. In the main most books will have gone through the editing process however some may not. We therefore suggest that you be aware of this before ordering this book. If in doubt check either the author or publisher’s details as we are unable to accept any returns unless they are faulty. Please contact us if you have any questions.

Understand data science concepts and methodologies to manage and deliver top-notch solutions for your organization

Key Features

Learn the basics of data science and explore its possibilities and limitations Manage data science projects and assemble teams effectively even in the most challenging situations Understand management principles and approaches for data science projects to streamline the innovation process

Book DescriptionData science and machine learning can transform any organization and unlock new opportunities. However, employing the right management strategies is crucial to guide the solution from prototype to production. Traditional approaches often fail as they don’t entirely meet the conditions and requirements necessary for current data science projects. In this book, you’ll explore the right approach to data science project management, along with useful tips and best practices to guide you along the way.

After understanding the practical applications of data science and artificial intelligence, you’ll see how to incorporate them into your solutions. Next, you will go through the data science project life cycle, explore the common pitfalls encountered at each step, and learn how to avoid them. Any data science project requires a skilled team, and this book will offer the right advice for hiring and growing a data science team for your organization. Later, you’ll be shown how to efficiently manage and improve your data science projects through the use of DevOps and ModelOps.

By the end of this book, you will be well versed with various data science solutions and have gained practical insights into tackling the different challenges that you’ll encounter on a daily basis.

What you will learn

Understand the underlying problems of building a strong data science pipeline Explore the different tools for building and deploying data science solutions Hire, grow, and sustain a data science team Manage data science projects through all stages, from prototype to production Learn how to use ModelOps to improve your data science pipelines Get up to speed with the model testing techniques used in both development and production stages

Who this book is forThis book is for data scientists, analysts, and program managers who want to use data science for business productivity by incorporating data science workflows efficiently. Some understanding of basic data science concepts will be useful to get the most out of this book.

Read More
Format
Paperback
Publisher
Packt Publishing Limited
Country
United Kingdom
Date
12 November 2019
Pages
290
ISBN
9781838826321