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Managing Data Science. Effective strategies to manage data science projects and build a sustainable team Kirill Dubovikov

Język publikacji: angielskim
Managing Data Science. Effective strategies to manage data science projects and build a sustainable team Kirill Dubovikov - okladka książki

Managing Data Science. Effective strategies to manage data science projects and build a sustainable team Kirill Dubovikov - okladka książki

Autor:
Kirill Dubovikov
Ocena:
Bądź pierwszym, który oceni tę książkę
Stron:
290
Dostępne formaty:
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     ePub
     Mobi

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Prezent last minute w ebookpoint.pl
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.

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O autorze książki

Kirill Dubovikov works as a CTO for Cinimex DataLab. He has more than 10 years of experience in architecting and developing complex software solutions for top Russian banks. Now, he leads the company's data science branch. His team delivers practical machine learning applications to businesses across the world. Their solutions cover an extensive list of topics, such as sales forecasting and warehouse planning, natural language processing (NLP) for IT support centers, algorithmic marketing, and predictive IT operations.

Kirill is a happy father of two boys. He loves learning all things new, reading books, and writing articles for top Medium publications.

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