Book Image

Managing Data Science

By : Kirill Dubovikov
Book Image

Managing Data Science

By: Kirill Dubovikov

Overview of this book

Data 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.
Table of Contents (18 chapters)
Free Chapter
1
Section 1: What is Data Science?
5
Section 2: Building and Sustaining a Team
9
Section 3: Managing Various Data Science Projects
14
Section 4: Creating a Development Infrastructure

Exploring machine learning

Now that you understand the general flow of thought on how to define learning processes using mathematics and statistics, we can explore the inner workings of machine learning. Machine learning studies algorithms and statistical models that are able to learn and perform specific tasks without explicit instruction. As every software development manager should have some expertise in computer programming, the data science project manager should understand machine learning. Grasping the underlying concepts between any machine learning algorithm will allow you to understand better the limitations and requirements for your project. It will ease communication and improve understanding between you and the data scientists on your team. Knowledge of basic machine learning terminology will make you speak in the language of data science.

We will now dive into the...