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Advanced Interdisciplinary Applications of Machine Learning Python Libraries for Data Science - Rilegato
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"This book will help emerging data scientist to gain hands on skills needed through real world data and completely up to date Python code. This book covers all the technical details right from installing the needed software to importing libraries and using latest data sets, deciding on the right model, training and testing, evaluation of the model. It will also cover NumPy, Pandas and matplotlib. It covers various machine learning like Regression, linear and logical Regression, Classification, SVM (support Vector Machine), clustering, KNearest Neighbor, Market basket analysis, Apriori, K Means clustering, Visualization using Seaborne. None of the existing books in the field covers all the essential algorithms with practical implementation and code in Python with all needed libraries and provides links to datasets used"--
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Advanced Interdisciplinary Applications of Machine Learning Python Libraries for Data Science
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Advanced Interdisciplinary Applications of Machine Learning Python Libraries for Data Science
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Advanced Interdisciplinary Applications of Machine Learning Python Libraries for Data Science
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Buch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The world is approaching a point where big data will start to play a beneficial role in many industries and organizations. Today, analyzing data for new insights has become an everyday norm, increasing the need for data analysts to use efficient and appropriate tools to provide quick and valuable results to clients. Existing research in the field currently lacks a full coverage of all essential algorithms, leaving a knowledge void for practical implementation and code in Python with all needed libraries and links to datasets used. Advanced Interdisciplinary Applications of Machine Learning Python Libraries for Data Science serves as a one-stop book to help emerging data scientists gain hands-on skills needed through real-world data and completely up-to-date Python code. It covers all the technical details, from installing the needed software to importing libraries and using the latest data sets; deciding on the right model; training, testing, and evaluating the model; and including NumPy, Pandas, and matplotlib. With coverage on various machine learning algorithms like regression, linear and logical regression, classification, support vector machine (SVM), clustering, k-nearest neighbor, market basket analysis, Apriori, k-means clustering, and visualization using Seaborne, it is designed for academic researchers, undergraduate students, postgraduate students, executive education program leaders, and practitioners. Codice articolo 9781668486962
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