Managing Data Science: Effective strategies to manage data science projects and build a sustainable team
Authors: Kirill Dubovikov
ISBN-10: 1838826327
ISBN-13: 9781838826321
Publication Date 出版日期: 2019-11-12
Print Length 页数: 290 pages
Book Description
By finelybook
Understand the concepts and methodologies to manage and deliver top-notch data science solutions for your organization
Data Science and Machine Learning can transform any organization and open new opportunities. A substantial managerial effort is needed to guide the solution from prototype development to production. Traditional approaches often fail as they have different conditions and requirements in mind. This book presents an approach to a data science project management,with tips and best practices to guide you along the way.
With the help of this book,you will understand the practical applications of data science and AI to incorporate them into your solutions. 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 balanced skillful team,and this book will present advice for hiring and growing a data science team for your organization. The book also shows you how to efficiently manage and improve your data science projects through the use of DevOps and ModelOps.
By the end of the book,the readers will have the practical knowledge to tackle various challenges they deal on a daily basis and will have an understanding of various data science solutions.
What you will learn
Understand the underlying problems of building a strong data science pipeline
Learn the different tools to build and deploy data science solutions
Hire,grow,and sustain an efficient data science team
Manage data science projects through all stages from prototype to production
Learn how to use ModelOps for improving data science projects
Master the model testing techniques used in both development and production stages
Contents
Preface
Section 1: What is Data Science?
Chapter 1: What You Can Do with Data Science
Chapter 2: Testing Your Models
Chapter 3: Understanding Al
Section 2: Building and Sustaining a Team
Chapter 4: An ldeal Data Science Team
Chapter 5: Conducting Data Science Interviews
Chapter 6: Building Your Data Science Team
Section 3: Managing Various Data Science Projects
Chapter 7: Managing Innovation
Chapter 8: Managing Data Science Projects
Chapter 9: Common Pitfalls of Data Science Projects
Chapter 10: Creating Products and Improving Reusability
Section 4: Creating a Development Infrastructure
Chapter 11: Implementing ModelOps
Chapter 12: Building Your Technology Stack
Chapter 13: Conclusion
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Index
