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\u003cp\u003e\u003cb\u003eLearn the fundamentals of statistics and machine learning using R libraries for data processing, visualization, model training, and statistical inference\u003c/b\u003e\u003c/p\u003e\u003ch4\u003eKey Features\u003c/h4\u003e\u003cul\u003e\u003cli\u003eAdvance your ML career with the help of detailed explanations, intuitive illustrations, and code examples\u003c/li\u003e\u003cli\u003eGain practical insights into the real-world applications of statistics and machine learning\u003c/li\u003e\u003cli\u003eExplore the technicalities of statistics and machine learning for effective data presentation\u003c/li\u003e\u003cli\u003ePurchase of the print or Kindle book includes a free PDF eBook\u003c/li\u003e\u003c/ul\u003e\u003ch4\u003eBook Description\u003c/h4\u003eThe Statistics and Machine Learning with R Workshop is a comprehensive resource packed with insights into statistics and machine learning, along with a deep dive into R libraries. The learning experience is further enhanced by practical examples and hands-on exercises that provide explanations of key concepts.\nStarting with the fundamentals, youâll explore the complete model development process, covering everything from data pre-processing to model development. In addition to machine learning, youâll also delve into R's statistical capabilities, learning to manipulate various data types and tackle complex mathematical challenges from algebra and calculus to probability and Bayesian statistics. Youâll discover linear regression techniques and more advanced statistical methodologies to hone your skills and advance your career.\nBy the end of this book, you'll have a robust foundational understanding of statistics and machine learning. Youâll also be proficient in using R's extensive libraries for tasks such as data processing and model training and be well-equipped to leverage the full potential of R in your future projects.\u003ch4\u003eWhat you will learn\u003c/h4\u003e\u003cul\u003e\u003cli\u003eHone your skills in different probability distributions and hypothesis testing\u003c/li\u003e\u003cli\u003eExplore the fundamentals of linear algebra and calculus\u003c/li\u003e\u003cli\u003eMaster crucial statistics and machine learning concepts in theory and practice\u003c/li\u003e\u003cli\u003eDiscover essential data processing and visualization techniques\u003c/li\u003e\u003cli\u003eEngage in interactive data analysis using R\u003c/li\u003e\u003cli\u003eUse R to perform statistical modeling, including Bayesian and linear regression\u003c/li\u003e\u003c/ul\u003e\u003ch4\u003eWho this book is for\u003c/h4\u003eThis book is for beginner to intermediate-level data scientists, undergraduate to masters-level students, and early to mid-senior data scientists or analysts looking to expand their knowledge of machine learning by exploring various R libraries. Basic knowledge of linear algebra and data modeling is a must. |
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