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Text as Data: A New Framework for Machine Learning and the Social Sciences

the way science and business are conducted. Text as Data shows how to combine new sources of data, machine learning tools, and social science;

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Text as Data

the way science and business are conducted. Text as Data shows how to combine new sources of data, machine learning tools, and social science;

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Big Data and Social Science

, statistics, and computer science as well as the field of data science provide a unique perspective on how to apply modern social science research;

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Big Data and Social Science

, statistics, and computer science as well as the field of data science provide a unique perspective on how to apply modern social science research;

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Social sciences via network analysis and computation

in network analysis, machine learning, data mining, data clustering and classifications in the contents of social sciences. It also covers various;

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Applied Directional Statistics

of attention due to demands from disciplines such as life sciences or machine learning, the availability of massive data sets requiring adapted;

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Machine Learning Methods in the Environmental Sciences

is the first single-authored textbook providing a unified treatment of machine learning methods and their applications in the environmental;

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Machine Learning Methods in the Environmental Sciences

is the first single-authored textbook providing a unified treatment of machine learning methods and their applications in the environmental;

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Handbook of Computational Social Science - Vol 1 & Vol 2

advances in data science, statistical modeling, and machine learning. It covers a range of key issues, including the management of big data;

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Data-Driven Science and Engineering

trains mathematical scientists and engineers for the next generation of scientific discovery by offering a broad overview of the growing;

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Machine Learning for Text

Text analytics is a field that lies on the interface of information retrieval,machine learning, and natural language processing, and this;

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Machine Learning for Text

Text analytics is a field that lies on the interface of information retrieval,machine learning, and natural language processing, and this;

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5th International Symposium on Data Mining Applications

The 5th Symposium on Data Mining Applications (SDMA 2018) provides valuable opportunities for technical collaboration among data mining and;

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Machine Learning Paradigms

sciences and technologies, brought together by non-traditional data collection and analysis, drive the digital economy at all levels and offer new;

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R

specialized machine learning techniques for text mining, social network data, big data, and more * Discover the different types of machine learning;

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Intelligent Information and Database Systems

in Information Sciences; IT in Biomedicine; Intelligent Technologies in the Smart Cities in the 21st Century; Analysis of Image, Video and Motion Data;

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Data Science Solutions with Python

, and XGBoost, and a deep learning (DL) framework known as Keras. The book starts off presenting supervised and unsupervised ML and DL models;

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Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data

learning text and as a reference book. Professors can readily use it for classes on data mining, Web mining, and text mining. Additional teaching;

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Machine Learning with PySpark

machine learning models such as K-means and hierarchical clustering. A major portion of the book focuses on feature engineering to create useful;

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Data Classification

areas as pattern recognition, database, data mining, and machine learning. Addressing the work of these different communities in a unified way;

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Data Classification

areas as pattern recognition, database, data mining, and machine learning. Addressing the work of these different communities in a unified way;

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Hands-On Automated Machine Learning

you're a budding data scientist, data analyst, or Machine Learning enthusiast and are new to the concept of automated machine learning, this book;

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Introduction to Machine Learning with Python

the steps necessary to create a successful machine-learning application with Python and the scikit-learn library. Authors Andreas Muller and;

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Machine Learning with Spark -

powerful tools to load, analyze, clean, and transform your data Who This Book Is For If you have a basic knowledge of machine learning and;

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Machine Learning The New AI

so as to maximize reward and minimize penalty. Alpaydin then considers some future directions for machine learning and the new field of data;

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Large-Scale Machine Learning in the Earth Sciences

From the Foreword: While large-scale machine learning and data mining have greatly impacted a range of commercial applications, their;

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Feature Engineering for Machine Learning and Data Analytics

depends on the quality of the available features. Feature Engineering for Machine Learning and Data Analytics provides a comprehensive;

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