Step-by-step recipes filled with practical code samples and engaging examples demonstrate Haskell in practice, and then the concepts behind the code.This book shows functional developers and analysts how to leverage their existing knowledge of Haskell specifically for high-quality data analysis. A good understanding of data sets and functional programming is assumed.

Binary analysis is the process of examining a binary program to determine information security actions. It is a complex, constantly evolving, and challenging topic that crosses over into several domains of information technology and security. This binary analysis book is designed to help you get started with the basics, before gradually advancing to challenging topics. Using a recipe-based approach, this book guides you through building a lab of virtual machines and installing tools to analyze binaries effectively. You'll begin by learning about the IA32 and ELF32 as well as IA64 and ELF64 specifications. The book will then guide you in developing a methodology and exploring a variety of tools for Linux binary analysis. As you advance, you'll learn how to analyze malicious 32-bit and 64-bit binaries and identify vulnerabilities. You'll even examine obfuscation and anti-analysis techniques, analyze polymorphed malicious binaries, and get a high-level overview of dynamic taint analysis and binary instrumentation concepts. By the end of the book, you'll have gained comprehensive insights into binary analysis concepts and have developed the foundational skills to confidently delve into the realm of binary analysis.

This book is for programmers, scientists, and engineers who have knowledge of the Python language and know the basics of data science. It is for those who wish to learn different data analysis methods using Python and its libraries. This book contains all the basic ingredients you need to become an expert data analyst.

Each chapter of the book quickly introduces a key ‘theme’ of Data Analysis, before immersing you in the practical aspects of each theme. You’ll learn quickly how to perform all aspects of Data Analysis.Practical Data Analysis is a book ideal for home and small business users who want to slice dice the data they have on hand with minimum hassle.

This third edition of a classic textbook presents a comprehensive introduction to Bayesian data analysis. Written for students and researchers alike, the text is written in an easily accessible manner with chapters that contain many exercises as well as detailed worked examples taken from various disciplines. This third edition provides two new chapters on Bayesian nonparametri...(展开全部)

Ivan Idris，实验物理学硕士，学位论文侧重于应用计算机科学。毕业后，他曾经效力于多家公司，从事Java开发、数据仓库开发以及QA分析等方面的工作；目前，他的兴趣主要集中在商业智能、大数据和云计算等专业领域。 Ivan Idris以编写简洁可测试的程序代码以及撰写有趣的技术文章为乐，同时也是Packt出版社NumPy Beginner's Guide-Second Edition、NumPy Cookbook和Learning NumPy Array等书籍的作者。读者可以访问ivanidris.net获取更多关于他的信息。

If you are a student or Java developer or a budding data scientist who wishes to learn the fundamentals of data analysis and learn to perform data analysis with Java, this book is for you. Some familiarity with elementary statistics and relational databases will be helpful but is not mandatory, to get the most out of this book. A firm understanding of Java is required.

Andrew Gelman, John B. Carlin, Hal S. Stern, Donald B. Rubin, David B. Dunson

Praise for the Second Edition: "A must-have book for anyone expecting to do research and/or applications in categorical data analysis". ("Statistics in Medicine"). "It is a total delight reading this book". ("Pharmaceutical Research"). "If you do any analysis of categorical data, this is an essential desktop reference". ("Technometrics"). The use of statistical methods for anal...(展开全部)