{"product_id":"machine-learning-with-r-by-brett-lantz","title":"Machine Learning with R\nby Brett Lantz","description":"\u003cp\u003eUse R and tidyverse to prepare, clean, import, visualize, transform, program, communicate, predict and model data\u003c\/p\u003e\n\n\u003cp\u003eNo R experience is required, although prior exposure to statistics and programming is helpful\u003c\/p\u003e\n\n\u003cp\u003ePurchase of the print or Kindle book includes a free eBook in PDF format.\u003c\/p\u003e\n\n\u003cp\u003eKey Features\u003cbr\u003e\nGet to grips with the tidyverse, challenging data, and big data\u003cbr\u003e\nCreate clear and concise data and model visualizations that effectively communicate results to stakeholders\u003cbr\u003e\nSolve a variety of problems using regression, ensemble methods, clustering, deep learning, probabilistic models, and more\u003cbr\u003e\nBook Description\u003cbr\u003e\nDive into R with this data science guide on machine learning (ML). Machine Learning with R, Fourth Edition, takes you through classification methods like nearest neighbor and Naive Bayes and regression modeling, from simple linear to logistic.\u003c\/p\u003e\n\n\u003cp\u003eDive into practical deep learning with neural networks and support vector machines and unearth valuable insights from complex data sets with market basket analysis. Learn how to unlock hidden patterns within your data using k-means clustering.\u003c\/p\u003e\n\n\u003cp\u003eWith three new chapters on data, you’ll hone your skills in advanced data preparation, mastering feature engineering, and tackling challenging data scenarios. This book helps you conquer high-dimensionality, sparsity, and imbalanced data with confidence. Navigate the complexities of big data with ease, harnessing the power of parallel computing and leveraging GPU resources for faster insights.\u003c\/p\u003e\n\n\u003cp\u003eElevate your understanding of model performance evaluation, moving beyond accuracy metrics. With a new chapter on building better learners, you’ll pick up techniques that top teams use to improve model performance with ensemble methods and innovative model stacking and blending techniques.\u003c\/p\u003e\n\n\u003cp\u003eMachine Learning with R, Fourth Edition, equips you with the tools and knowledge to tackle even the most formidable data challenges. Unlock the full potential of machine learning and become a true master of the craft.\u003c\/p\u003e\n\n\u003cp\u003eWhat you will learn\u003cbr\u003e\nLearn the end-to-end process of machine learning from raw data to implementation\u003cbr\u003e\nClassify important outcomes using nearest neighbor and Bayesian methods\u003cbr\u003e\nPredict future events using decision trees, rules, and support vector machines\u003cbr\u003e\nForecast numeric data and estimate financial values using regression methods\u003cbr\u003e\nModel complex processes with artificial neural networks\u003cbr\u003e\nPrepare, transform, and clean data using the tidyverse\u003cbr\u003e\nEvaluate your models and improve their performance\u003cbr\u003e\nConnect R to SQL databases and emerging big data technologies such as Spark, Hadoop, H2O, and TensorFlow\u003cbr\u003e\nWho this book is for\u003cbr\u003e\nThis book is designed to help data scientists, actuaries, data analysts, financial analysts, social scientists, business and machine learning students, and any other practitioners who want a clear, accessible guide to machine learning with R. No R experience is required, although prior exposure to statistics and programming is helpful.\u003c\/p\u003e\n\n\u003cp\u003eTable of Contents\u003cbr\u003e\nIntroducing Machine Learning\u003cbr\u003e\nManaging and Understanding Data\u003cbr\u003e\nLazy Learning – Classification Using Nearest Neighbors\u003cbr\u003e\nProbabilistic Learning – Classification Using Naive Bayes\u003cbr\u003e\nDivide and Conquer – Classification Using Decision Trees and Rules\u003cbr\u003e\nForecasting Numeric Data – Regression Methods\u003cbr\u003e\nBlack-Box Methods – Neural Networks and Support Vector Machines\u003cbr\u003e\nFinding Patterns – Market Basket Analysis Using Association Rules\u003cbr\u003e\nFinding Groups of Data – Clustering with k-means\u003cbr\u003e\nEvaluating Model Performance\u003cbr\u003e\nBeing Successful with Machine Learning\u003cbr\u003e\n(N.B. Please use the Look Inside option to see further chapters)\u003c\/p\u003e","brand":"Books Feri","offers":[{"title":"Premium Paperback","offer_id":45614018330815,"sku":null,"price":535.0,"currency_code":"BDT","in_stock":true},{"title":"Premium Hardcover","offer_id":45614079082687,"sku":null,"price":635.0,"currency_code":"BDT","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0692\/8148\/0895\/files\/61coYj6wrQL.jpg?v=1777959746","url":"https:\/\/booksferi.store\/products\/machine-learning-with-r-by-brett-lantz","provider":"Books Feri","version":"1.0","type":"link"}