Machine Learning in R. Expert Techniques for Predictive Analysis
The R language offers a powerful set of machine learning methods that allow for quick non-trivial analysis of your data. This book serves as a guide to applying machine learning methods to solve everyday tasks. Brett Lantz will teach you...
everything you need for data analysis, forecasting, and data visualization. Here you will find information about new improved libraries, advice on the ethical aspects of machine learning and bias issues, as well as an introduction to deep learning. This book covers - The basics of machine learning and the features of computer training with examples. - Data preparation for use in machine learning using R. - Classification of result significance. - Event prediction using decision trees, rules, and support vectors. - Forecasting numerical data and assessing financial data using regression methods. - Modeling complex processes using neural networks – the foundation of deep learning. - Model evaluation and performance improvement. - The latest technologies for big data processing, including R 3.6, Spark, H2O, and TensorFlow.
The R language offers a powerful set of machine learning methods that allow for quick non-trivial analysis of your data. This book serves as a guide to applying machine learning methods to solve everyday tasks. Brett Lantz will teach you everything you need for data analysis, forecasting, and data visualization. Here you will find information about new improved libraries, advice on the ethical aspects of machine learning and bias issues, as well as an introduction to deep learning. This book covers - The basics of machine learning and the features of computer training with examples. - Data preparation for use in machine learning using R. - Classification of result significance. - Event prediction using decision trees, rules, and support vectors. - Forecasting numerical data and assessing financial data using regression methods. - Modeling complex processes using neural networks – the foundation of deep learning. - Model evaluation and performance improvement. - The latest technologies for big data processing, including R 3.6, Spark, H2O, and TensorFlow.
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In stock
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