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The author explains the internal logic embodied in the Python language so that readers can get into the Python mindset and make better design choices in their codes, which is especially helpful for newcomers to both Python and data analysis.
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This book provides a detailed description of machine learning algorithms in Data Analytics, Data Science Lifecycle, Python for Machine... Læs mere
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This book focuses on various authorization and access control techniques, threats and attack modelling including overview of open... Læs mere
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Text Analytics: An Introduction to the Science and Applications of Unstructured Information Analysis... Læs mere
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Text Analytics: An Introduction to the Science and Applications of Unstructured Information Analysis... Læs mere
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From data collection to evaluation and visualization of prediction results, this book provides a comprehensive overview of the process of predicting demand for retailers.
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This textbook provides a compact but comprehensive treatment that provides analytical and design steps to recurrent neural networks from scratch.
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Data Science: An Introduction focuses on using the R programming language in Jupyter notebooks to perform basic data manipulation and cleaning, create effective visualizations, and extract insights from data using supervised predictive models.
Bemærk: Kan ikke leveres før jul.
Data Science: An Introduction focuses on using the R programming language in Jupyter notebooks to perform basic data manipulation and cleaning, create effective visualizations, and extract insights from data using supervised predictive models.
Bemærk: Kan ikke leveres før jul.
Data analytics underpin our modern data-driven economy. This textbook explains the relevance of data analytics at the firm and industry levels, tracing the evolution and key components of the field and showing how data analytics insights can be leveraged for business results.
Bemærk: Kan ikke leveres før jul.
Data analytics underpin our modern data-driven economy. This textbook explains the relevance of data analytics at the firm and industry levels, tracing the evolution and key components of the field and showing how data analytics insights can be leveraged for business results.
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This book aims to provide theoretical and empirical frameworks and highlights the challenges and solutions with using Big Data for Corporate Social Responsibility (CSR) and Sustainability in the field of digital transformation and tourism.