Statistics with R for Machine Learning: Volume 1 Data Preparation and Splitting with R for Machine Learning
Author: Mohsen Nady
Publisher finelybook 出版社: Arcler Press
Edition 版本: N/A
Publication Date 出版日期: 2025-01-10
Language 语言: English
Print Length 页数: 295 pages
ISBN-10: 1779564708
ISBN-13: 9781779564702
Book Description
Data preparation is the foundation of any successful machine learning project. This volume provides a comprehensive guide to cleaning, transforming, and splitting data for machine learning using R, including handling missing values, feature scaling, and stratified sampling. Practical examples and R code demonstrate how to optimize datasets for predictive modeling. The volume is essential for data scientists and machine learning practitioners seeking to build robust models.
About the Author
Mohsen Nady is a pharmacist with a M.D. in Microbiology and a Diploma in Industrial Pharmacy. Besides, Mohsen has more than 10 years of experience in Statistics and Data Analytics. Mohsen has applied his skills to different projects related to Genomics, Microbiology, Biostatistics, Six Sigma, Data Analytics, Data Visualization, Building Apps, Geography, Market Analysis, Business Analysis, Machine Learning, etc. Mohsen also published his thesis in a high-impact journal that attracted many citations, where all the statistical analyses were performed by him in addition to the methodological part. Furthermore, Mohsen has earned different certificates, from top universities (Harvard, Johns Hopkins, Denmark, etc) in Statistics, Data Analytics, Data Visualization, and Machine Learning that highlight his outstanding diverse skills.
下载地址
PDF | 5 MB | 2025-05-01
未经允许不得转载:finelybook » Statistics with R for Machine Learning: Volume 1 Data Preparation and Splitting with R for Machine Learning
相关推荐
ChatGPT: Principles and Architecture
Digital Transformation Best Practices: Empower your business with data-driven strategies and Agile technologies
Google Cloud Architect Handbook: Designing highly available and resilient architectures on Google Cloud
Generative AI with Kubernetes: Implementing secure and observable AI infrastructure to deliver reliable AI applications
Data Analysis with LLMs: Text, tables, images and sound
Advanced Mathematical Techniques in Science and Engineering
评论 抢沙发
觉得文章有用就打赏一下
您的打赏,我们将继续给力更多优质内容
支付宝扫一扫

微信扫一扫
