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Data Science for Business with R focuses on the concepts foundational for students starting a business analytics or data science course;
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of a business' operations. SMEs are looking for ways to use data science and analytics, and this need is becoming increasingly pressing with;
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of a business' operations. SMEs are looking for ways to use data science and analytics, and this need is becoming increasingly pressing;
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demand for new projects, using Monte Carlo simulation to understand outcome distribution, among other topics. The data science methods covered;
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handling of polyglot data types in a data lake for repeatable results Who This Book Is For Data scientists and data engineers who are required to;
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, principals, and best practices that you need know for best-in-class business data science.;
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data mining in everyday business environments is imperative to the success of modern businesses. Utilizing Big Data Paradigms for Business;
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This book combines the analytic principles of digital business and data science with business practice and big data. The interdisciplinary;
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, Machine Learning, and Big Data - That You Don't Data Science for Business: Predictive Modeling, Data Mining, Data Analytics, Data Warehousing;
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Data science has a huge impact on how companies conduct business, and those who don't learn about this revolutionaryfield could be left;
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big data. How are they doing it? Data Science Strategy For Dummies answers all your questions about how to build a data science capability;
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, mathematics, machine learning, and computer science, for most non-academics, data science looks like applying analysis techniques to answer key;
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, data science techniques and their applications - and gradually build up to building a professional reference operating model for a data science;
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than existing books by applying data to decision making. Not only is the book useful for undergraduates, but it can also help business owners;
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What if there was one simple, clear process for ensuring that all your company's data science projects achieve a high a return on investment;
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intelligent agents. In Part II, he describes the main steps in creating AI-based data science solutions for business problems, including problem;
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intelligent agents. In Part II, he describes the main steps in creating AI-based data science solutions for business problems, including problem;
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majority fail. These expensive quagmires can be avoided, and this book explains precisely how. Data science is emerging as a hands-on tool for;
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for any organization that collects, stores and processes data as part of its operations. This book is ideal for business users, data analysts;
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technologies in various domains are still evolving. For instance, the explosive growth in big data and social media analytics requires examination;
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intelligence, machine learning, data science and big data analytics to look for new techniques in business analytics and applications of artificial;
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intelligence, machine learning, data science and big data analytics to look for new techniques in business analytics and applications of artificial;
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This edited volume is brought out from the contributions of the research papers presented in the International Conference on Data Science;
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demand for machine learning and analysis, this new edition boasts additional R tools, modeling techniques, and more. Practical Data;
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: You should mine your own company for talent. You can't change your organization by hiring a few data science superheroes. You should form;
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contributions from leading experts and covers cutting-edge topics such as smart data and cloud computing, AI for networking, smart data deep learning;
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