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Data Science - volgomoda.ru
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Data Science


Data Science

899 RUR
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Data Science


Data Science

799 RUR
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Data Science


Data Science

799 RUR
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Data Science


Data Science

2499 RUR
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Data Science


Data Science

2399 RUR
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Data Science


Data Science

2499 RUR
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Data Science


Data Science

2399 RUR
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Lillian Pierson Data Science For Dummies


Discover how data science can help you gain in-depth insight into your business – the easy way! Jobs in data science abound, but few people have the data science skills needed to fill these increasingly important roles. Data Science For Dummies is the perfect starting point for IT professionals and students who want a quick primer on all areas of the expansive data science space. With a focus on business cases, the book explores topics in big data, data science, and data engineering, and how these three areas are combined to produce tremendous value. If you want to pick-up the skills you need to begin a new career or initiate a new project, reading this book will help you understand what technologies, programming languages, and mathematical methods on which to focus. While this book serves as a wildly fantastic guide through the broad, sometimes intimidating field of big data and data science, it is not an instruction manual for hands-on implementation. Here’s what to expect: Provides a background in big data and data engineering before moving on to data science and how it's applied to generate value Includes coverage of big data frameworks like Hadoop, MapReduce, Spark, MPP platforms, and NoSQL Explains machine learning and many of its algorithms as well as artificial intelligence and the evolution of the Internet of Things Details data visualization techniques that can be used to showcase, summarize, and communicate the data insights you generate It's a big, big data world out there—let Data Science For Dummies help you harness its power and gain a competitive edge for your organization.

2232.08 RUR

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Field Cady Data Science


Tap into the power of data science with this comprehensive resource for non-technical professionals Data Science: The Executive Summary – A Technical Book for Non-Technical Professionals  is a comprehensive resource for people in non-engineer roles who want to fully understand data science and analytics concepts. Accomplished data scientist and author Field Cady describes both the “business side” of data science, including what problems it solves and how it fits into an organization, and the technical side, including analytical techniques and key technologies.  Data Science: The Executive Summary covers topics like:  Assessing whether your organization needs data scientists, and what to look for when hiring them When Big Data is the best approach to use for a project, and when it actually ties analysts’ hands Cutting edge Artificial Intelligence, as well as classical approaches that work better for many problems How many techniques rely on dubious mathematical idealizations, and when you can work around them Perfect for executives who make critical decisions based on data science and analytics, as well as mangers who hire and assess the work of data scientists, Data Science: The Executive Summary also belongs on the bookshelves of salespeople and marketers who need to explain what a data analytics product does. Finally, data scientists themselves will improve their technical work with insights into the goals and constraints of the business situation.  

6840.76 RUR

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О'Нил Кэтрин Data Science. Инсайдерская информация для новичков. Включая язык R


Вводная книга о Data Science с описанием важнейших алгоритмов, принципов обработки данных, постановки и решения задач

1523 RUR

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Field Cady Data Science

John Paul Mueller Data Science Programming All-in-One For Dummies


Your logical, linear guide to the fundamentals of data science programming Data science is exploding—in a good way—with a forecast of 1. 7 megabytes of new information created every second for each human being on the planet by 2020 and 11. 5 million job openings by 2026. It clearly pays dividends to be in the know. This friendly guide charts a path through the fundamentals of data science and then delves into the actual work: linear regression, logical regression, machine learning, neural networks, recommender engines, and cross-validation of models. Data Science Programming All-In-One For Dummies is a compilation of the key data science, machine learning, and deep learning programming languages: Python and R. It helps you decide which programming languages are best for specific data science needs. It also gives you the guidelines to build your own projects to solve problems in real time. Get grounded: the ideal start for new data professionals What lies ahead: learn about specific areas that data is transforming Be meaningful: find out how to tell your data story See clearly: pick up the art of visualization Whether you’re a beginning student or already mid-career, get your copy now and add even more meaning to your life—and everyone else’s!

3041.52 RUR

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Cole Stryker Smarter Data Science


Organizations can make data science a repeatable, predictable tool, which business professionals use to get more value from their data Enterprise data and AI projects are often scattershot, underbaked, siloed, and not adaptable to predictable business changes. As a result, the vast majority fail. These expensive quagmires can be avoided, and this book explains precisely how.  Data science is emerging as a hands-on tool for not just data scientists, but business professionals as well. Managers, directors, IT leaders, and analysts must expand their use of data science capabilities for the organization to stay competitive. Smarter Data Science helps them achieve their enterprise-grade data projects and AI goals. It serves as a guide to building a robust and comprehensive information architecture program that enables sustainable and scalable AI deployments. When an organization manages its data effectively, its data science program becomes a fully scalable function that’s both prescriptive and repeatable. With an understanding of data science principles, practitioners are also empowered to lead their organizations in establishing and deploying viable AI. They employ the tools of machine learning, deep learning, and AI to extract greater value from data for the benefit of the enterprise. By following a ladder framework that promotes prescriptive capabilities, organizations can make data science accessible to a range of team members, democratizing data science throughout the organization. Companies that collect, organize, and analyze data can move forward to additional data science achievements: Improving time-to-value with infused AI models for common use cases Optimizing knowledge work and business processes Utilizing AI-based business intelligence and data visualization Establishing a data topology to support general or highly specialized needs Successfully completing AI projects in a predictable manner Coordinating the use of AI from any compute node. From inner edges to outer edges: cloud, fog, and mist computing When they climb the ladder presented in this book, businesspeople and data scientists alike will be able to improve and foster repeatable capabilities. They will have the knowledge to maximize their AI and data assets for the benefit of their organizations.

3806.35 RUR

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Data Science. Инсайдерская информация для новичков. Включая язык R


Data Science (исследование данных) - одна из самых востребованных специализаций нашего времени. Изучение данных позволяет преобразить любую традиционную или инновационную бизнес-модель. Эта книга основана на вводном курсе по Data Science из Колумбийского университета, и начинающему специалисту-аналитику она совершенно необходима. Эта книга увлекательно и доступно рассказывает оБайесовском методеСтатистических алгоритмахФинансовом моделированииРекомендательных движкахВизуализации данныхMapReduceс примерами на языках Python и R

1181 RUR

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Кэти О'Нил Data Science. Инсайдерская информация для новичков. Включая язык R.


Data Science (исследование данных) – одна из самых востребованных специализаций нашего времени. Изучение данных позволяет преобразить любую традиционную или инновационную бизнес-модель. Эта книга основана на вводном курсе по Data Science из Колумбийского университета, и начинающему специалисту-аналитику она совершенно необходима. Эта книга увлекательно и доступно рассказывает о: ● байесовском методе; ● статистических алгоритмах; ● финансовом моделировании; ● рекомендательных движках; ● визуализации данных; ● MapReduce.

550 RUR

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Группа авторов Big Data Meets Survey Science

Marcin Szeliga Data Science i uczenie maszynowe

Irene Aldridge Big Data Science in Finance

Cole Stryker Smarter Data Science

EMC Services Education Data Science and Big Data Analytics. Discovering, Analyzing, Visualizing and Presenting Data


Data Science and Big Data Analytics is about harnessing the power of data for new insights. The book covers the breadth of activities and methods and tools that Data Scientists use. The content focuses on concepts, principles and practical applications that are applicable to any industry and technology environment, and the learning is supported and explained with examples that you can replicate using open-source software. This book will help you: Become a contributor on a data science team Deploy a structured lifecycle approach to data analytics problems Apply appropriate analytic techniques and tools to analyzing big data Learn how to tell a compelling story with data to drive business action Prepare for EMC Proven Professional Data Science Certification Corresponding data sets are available at www.wiley.com/go/9781118876138. Get started discovering, analyzing, visualizing, and presenting data in a meaningful way today!

5624.15 RUR

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