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Free Download Introduction to Engineering Nonlinear and Parametric Vibrations with MATLAB and Maple by Alan B. Palazzolo, Dongil Shin, Jeffrey Falzarano
English | July 14, 2025 | ISBN: 1119319544 | 640 pages | MOBI | 60 Mb
Textbook on nonlinear and parametric vibrations discussing relevant terminology and analytical and computational tools for analysis, design, and troubleshooting

Free Download Introduction to Differential and Difference Equations through Modeling (Textbooks in Mathematics) by William P. Fox, Robert E. Burks Jr.
English | July 8, 2025 | ISBN: 1032949007 | 337 pages | MOBI | 13 Mb
This book presents an opportunity to learn difference and differential equations through a modeling-first approach. The text is meant as an introduction to those equations and not as a text only for modeling courses. No previous exposure to these equations is expected. Modeling in Introduction to Differential and Difference Equations through Modeling is presented as the vehicle for learning difference and differential equations.

Free Download Introduction to Data Science Using R: second edition
English | December 4, 2025 | ASIN: B0G55TKYLT | 505 pages | EPUB (True) | 32.86 MB
Dive into the world of data science with "Introduction to Data Science Using R, 2nd Edition." This comprehensive guide transcends conventional statistical and computer science textbooks by offering a fresh perspective on the essential skills needed for a successful career in data science. From demystifying basic statistics concepts to equipping you with fundamental programming abilities in R, this book is your gateway to understanding the distinctiveness and value of data science in contemporary organizations grappling with big data. Delve into the three core components of the book: an enlightening overview of data science's interdisciplinary nature, practical applications of machine learning algorithms for predictive insights, and hands-on R programming exercises tailored for aspiring data scientists. Unraveling the importance of data science through diverse real-world examples spanning various domains, this book seamlessly integrates statistical and machine learning theories with practical R programming commands. Embark on a journey of discovery with engaging case studies that blend statistical insights with business acumen, decision science, and data engineering prowess. Get ready to embark on a thrilling data science odyssey filled with knowledge, practical applications, and illuminating case studies in "Introduction to Data Science Using R, 2nd Edition." Contents: 1. Data Science: Key Concepts 2. Data Wrangling 3. Spotting Signals: An Overview 4.1. Introduction to R 4.2. Business Storytelling Using R 5.1. Problem based Analysis 5.2. Model 6.1. Bivariate Analysis 6.2. Cross Tabs 7. Correlation Matrix 8.1. Visualization and Visual Constructs 8.2. Advance Visualization 9.1. Machine Learning in Action 9.2. Decision Trees 9.3. Support Vector Machines 9.4. Naive Bayes 9.5. Linear Regression 9.6. Regression 9.7. A/B Testing 9.8. Classification 9.9. Introduction to Gradient Boosting 10.1. Sample Preparation 10.2. Data Train and Test Data 11.1. Multivariate Analysis Topics 11.2. Principal Component Analysis 11.3. Factor Analysis 11.4. ANOVA 12.1. Additional Topics in Analytics 12.2. Exploratory Data Analysis Case Study - Business Perspective 13. Text Mining

Free Download Introduction to Cryptography By Delfs H., Knebl H.
2002 | 80 Pages | ISBN: 0130614661 | PDF | 1 MB
Due to the rapid growth of digital communication and electronic data exchange, information security has become a crucial issue in industry, business, and administration. Modern cryptography provides essential techniques for securing information and protecting data.In the first part, this book covers the key concepts of cryptography on an undergraduate level, from encryption and digital signatures to cryptographic protocols. Essential techniques are demonstrated in protocols for key exchange, user identification, electronic elections and digital cash. In the second part, more advanced topics are addressed, such as the bit security of one-way functions and computationally perfect pseudorandom bit generators. The security of cryptographic schemes is a central topic. Typical examples of provably secure encryption and signature schemes and their security proofs are given. Though particular attention is given to the mathematical foundations, no special background in mathematics is presumed. The necessary algebra, number theory and probability theory are included in the appendix. Each chapter closes with a collection of exercises.The second edition contains corrections, revisions and new material, including a complete description of the AES, an extended section on cryptographic hash functions, a new section on random oracle proofs, and a new section on public-key encryption schemes that are provably secure against adaptively-chosen-ciphertext attacks.

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Introduction to Generative AI, Second Edition (MEAP V02)

Introduction to Generative AI, Second Edition (MEAP 06)

Introduction to Generative AI, Second Edition (Final)

Introduction to Facilities Management Foundational Skills for Effective Workplace Operations

Introduction to Engineering Nonlinear and Parametric Vibrations with MATLAB and Maple

Introduction to Differential and Difference Equations through Modeling (Textbooks in Mathematics)

Introduction to Data Science Using R second edition

Introduction to Cryptography

Introducing Python Modern Computing in Simple Packages, 3rd Edition (PDF)

Introducing Python Modern Computing in Simple Packages, 3rd Edition (EPUB)