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Ensemble Learning with R begins with the important statistical resampling methods. You will then walk through the central trilogy of ensemble;
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students of data mining and machine learning, Ensemble Classification Methods with Applications in R puts the focus on two topics in machine;
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Guides professionals and students through the rapidly growing field of machine learning with hands-on examples in the popular R programming;
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convenient resource on ensemble learning methods.;
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Hands-on Machine Learning with R provides a practical and applied approach to learning and developing intuition into today's most popular;
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quickly and easily gain insight from your data. Machine Learning with R, Third Edition provides a hands-on, readable guide to applying machine;
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learning architecture with ensemble learning Who This Book Is For Data scientists and machine learning engineers keen on;
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use each app. With an unmatched emphasis on learning outcomes and transference of skills, NEW PERSPECTIVES MICROSOFT (R) OFFICE 365;
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Use R for efficient data mining, text analytics and feature engineering Become a thorough data science professional with the help of hands-on;
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of ensemble machine learning such as boosting, bagging, and stacking. The Ensemble Machine Learning Cookbook will start by getting you acquainted with;
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an unmatched emphasis on learning outcomes and transference of skills, NEW PERSPECTIVES MICROSOFT (R) OFFICE 365 & EXCEL 2016: COMPREHENSIVE;
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. The final chapter contains a detailed end-to-end solution with neural networks in Pytorch. After completing Hands-on Machine Learning with;
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Productivity Apps provide a visual introduction to Microsoft (R) OneNote, Sway, Office Mix and Edge with fun, hands-on activities for active learning;
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. The final chapter contains a detailed end-to-end solution with neural networks in Pytorch. After completing Hands-on Machine Learning with;
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through deep learning and convolutional neural networks, deep learning with recurrent neural networks, big data with Hadoop (R), Spark (TM) and;
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includes topics such as environmental science and green issues. - Engage students through an active learning approach with hands-on activities to;
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includes topics such as environmental science and green issues. - Engage students through an active learning approach with hands-on activities to;
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Apps visually introduce Microsoft (R) OneNote, Sway, Office Mix and Edge with fun, hands-on activities for active learning. Companion Sways;
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Develop the Microsoft (R) PowerPoint (R) 2016 skills you need to be successful in college and beyond with the emphasis on critical-thinking;
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Behavior Analysis with Machine Learning Using R introduces machine learning and deep learning concepts and algorithms applied to a diverse;
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Develop the Microsoft (R) Office and Access 2016 skills you need to be successful in college and beyond with the emphasis on critical;
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support hands-on learning. Those R developers who want to integrate R in Tableau will also benefit from this book. What You Will Learn;
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