"Statistics with Rust, Second Edition" is designed to help you learn quickly, focusing on practical statistics using Rust scripts. The book is for readers who know the basics of statistics and machine learning. It gives quick explanations so you can try out concepts with hands-on coding. The book uses the newest version of Rust, 1.72.0 , to help users build and secure statistical and machine learning algorithms . Each chapter is full of useful programs and code examples that will walk you through tasks like data manipulation, statistical tests, regression analysis, building machine learning models, and natural language processing. This second edition brings all chapters up to date with the latest in stats and Rust programming. It focuses on how you can put these things to practical use, with a detailed look at advanced algorithms like PCA, SVM, neural networks, and ensemble methods . We've also included some natural language processing topics, such as text preprocessing, tokenization, and word embeddings. The book also shows you how to combine Rust's performance and safety with statistical analysis, giving you the tools you need to do data analysis efficiently and reliably. Table of Content Introduction to Rust for Statisticians Data Handling and Preprocessing Descriptive Statistics Probability Distributions and Random Variables Inferential Statistics Regression Analysis Bayesian Statistics Multivariate Statistical Methods Nonlinear Models and Machine Learning Model Evaluation and Validation Text and Natural Language Processing