Название: Using R for Introductory Statistics in Social Sciences
Автор: Mark A. Perkins
Издательство: Springer
Год: 2026
Страниц: 211
Язык: английский
Формат: pdf (true), epub
Размер: 33.0 MB

This book teaches R programming for fundamental statistical and data analysis skills, specifically tailored to social scientists and others new to quantitative research. Traditionally, this audience has relied on costly software packages such as SPSS, STATA, and SAS. However, R is a free, open-source alternative that, with proper guidance, is accessible and powerful for their needs. Many existing resources, whether books or online, are overly technical or difficult to follow. This book fills that gap by offering a concise, practical guide to mastering essential statistical processes, equipping readers with skills they can use throughout their careers. Data analysts, institutional researchers, and other professionals will use the book to perform statistical analyses and generate reports for their organizations. The included code—both in the book and online—helps them apply techniques to their own data. The Chapter 2 introduces readers to setting up R for statistical analysis, beginning with downloading and installing R base, the core engine for R, and RStudio, a versatile user interface that simplifies statistical analyses and programming tasks.

Название: Machine Learning Techniques to Solve Mechanical Vibration Problems Using Python
Автор: Baris Aykent
Издательство: Springer
Год: 2026
Страниц: 233
Язык: английский
Формат: pdf (true), epub
Размер: 12.3 MB

Machine vibrations hold the secrets to its health, but how do you translate their complex language into actionable, predictive intelligence? As modern industry demands unprecedented levels of reliability and efficiency, the ability to anticipate failures before they occur has become a critical competitive advantage. The key lies in the powerful intersection of classical engineering and modern Data Science. Machine Learning for Vibration Problems is the definitive guide for engineers, data scientists, and students looking to master this essential discipline. This comprehensive book bridges the gap between traditional vibration analysis and cutting-edge Machine Learning, guiding you step-by-step through the entire Prognostics and Health Management (PHM) workflow. Starting with the fundamentals of signal processing and feature engineering, you will learn to extract meaningful information from raw sensor data. From there, you will journey through a spectrum of algorithms—from interpretable models like Random Forests and SVMs to the powerhouses of Deep Learning. Master the application of Convolutional Neural Networks (CNNs) for automated feature extraction and Long Short-Term Memory (LSTM) networks for accurately predicting Remaining Useful Life (RUL). This book moves beyond theory, grounding every concept in practical application with detailed case studies on benchmark industrial datasets and a full annex of illustrative Python code.

Название: Engineering Trustworthy Software Systems: 7th International School, SETSS 2025, Beijing, China, May 17–23, 2025, Tutorial Lectures
Автор: Jonathan P. Bowen, Andrea Turrini
Издательство: Springer
Серия: Lecture Notes in Computer Science, 16481
Год: 2026
Страниц: 299
Язык: английский
Формат: pdf (true), epub
Размер: 56.4 MB

This book LNCS 16481 constitutes the refereed proceedings of the 7th International School on Engineering Trustworthy Software Systems, SETSS 2025, held in Beijing, China, in May 17–23, 2025. The 7 full papers were carefully reviewed and selected from 8 submissions. The proceedings focuses on lectures given during SETSS covered an ample variety of techniques to achieve this goal, from model checking to simulation testing, from the use of formal methods and contracts to model-based engineering. The common theme of the programme of SETSS 2025 was how to ensure that autonomous systems, whether robotic or involving Artificial Intelligence, operate as desired. The lectures given during SETSS covered an ample variety of techniques to achieve this goal, from model checking to simulation testing, from the use of formal methods and contracts to model-based engineering. The companion workshop offered an overview of the state of the art of the corresponding academic research. The sessions delved into foundational theories and practical methodologies, comprehensively exploring the subject. Neural Network-Controlled Systems (NNCSs), which embed deep neural networks into feedback control loops, are increasingly used in safety-critical domains such as autonomous driving, robotics, and industrial automation.

Название: From Data to Dollars: Getting Started with Data Analytics and AI in Startups
Автор: Piotr Sidoruk
Издательство: Apress
Год: 2026
Страниц: 557
Язык: английский
Формат: pdf, epub
Размер: 19.5 MB

Turn raw data into real traction—and real revenue. This practical hands-on guide is built for the realities of startup life—where time is short, resources are limited, and every decision counts. Whether you're just getting started or scaling fast, this book is your essential playbook for building a data-driven startup ready for growth and innovation—and for turning insight into impact and data into dollars. You’ll explore how to create a strong data foundation free from the rigidity of traditional corporate models, and how to use analytics and AI to inform product development, customer insights, and investor communication—ultimately turning data into measurable business outcomes and revenue growth. While SQL is the essential tool for accessing and retrieving data, Python and R provide the advanced capabilities required for in-depth statistical analysis, predictive modeling, and sophisticated data visualization. Python has emerged as the more popular choice for startup environments, while R maintains strong positioning in specialized domains requiring deep statistical expertise. The choice between these languages often reflects the professional background of the data team.

Название: CrewAI Practical Guide: Build Multi-Agent AI Workflows with Python: Hands-On Examples, Real Code, and Production -Ready Patterns for LLM-Powered Automation — No Theory Fluff
Автор: Nathan R. Cole
Издательство: Independently published
Год: 2026
Страниц: 228
Язык: английский
Формат: pdf, epub
Размер: 12.5 MB

The Book That Turns Confusing AI Agent Talk Into Deployable, Money-Making Workflows (No PhD Required). Are you tired of AI books that overpromise and underdeliver — stuffed with theory, but no real systems you can actually use? Do you feel overwhelmed by fragmented agent frameworks, endless docs, and lack of structure when trying to build multi-agent workflows? Have you spent hours hacking LangChain or AutoGen, only to end up with half-broken prototypes and no clear deployment path? In a world obsessed with abstract “intelligence,” the real win goes to those who know how to build structured, working, multi-agent workflows that ship — workflows that solve real problems, serve real users, and run in production. This is that book. You’ll Never Look at Agent Workflows the Same Way Again. Written for ambitious product builders, technical PMs, AI enthusiasts, and developers tired of fluff, CrewAI Practical Guide walks you step by step through the real patterns, components, and orchestration designs you need to create robust AI systems with Python — not just prompts or toy demos. This is the book your competitors hope you won’t read. CrewAI is written in Python and depends on Python 3.10 or newer. The easiest way to create a custom tool in CrewAI is by writing a Python function, then wrapping it using a tool decorator or class structure.

Название: Mastering Site Reliability Engineering in Enterprise: A Complete Guide to Resilient Systems & Chaos Engineering
Автор: Florian Hoeppner, Francesco Sbaraglia
Издательство: Apress
Год: 2025
Страниц: 326
Язык: английский
Формат: True PDF, True EPUB
Размер: 12.8 MB

Transform enterprise IT by adopting site reliability engineering (SRE) practices that reduce downtime, build resilience, and drive business value. This book is a comprehensive guide designed to help site reliability engineers, DevOps teams, and platform engineers identify, address, and mitigate system weaknesses before they become significant critical failures. Authors Francesco Sbaraglia and Florian Hoeppner highlight the paradigm shift from IT as a cost center to a core business function, emphasizing the central role of developers and the need for speed and reliability. Specific SRE capabilities like chaos engineering, observability, and toil management are explored, along with strategies for successful implementation, including building a Center of Excellence, selecting the right tools, and fostering a culture of collaboration and continuous improvement. By the end of this book, you’ll know how to apply core SRE practices to strengthen reliability: establishing a chaos engineering practice led by SREs, running reliability-focused “game days,” improving observability, troubleshooting failure scenarios, and fortifying the digital resilience of your systems and teams. For professionals, architects, engineers, and practitioners eager to design, plan and implement enterprise system resilience with proven SRE practices.

Название: An Open Guide to Data Structures and Algorithms
Автор: Paul W. Bible, Lucas Moser
Издательство: PALNI Open Press
Год: October 31, 2023
Страниц: 350
Язык: английский
Формат: pdf (true), epub
Размер: 22.0 MB

This textbook serves as a gentle introduction for undergraduates to theoretical concepts in data structures and algorithms in computer science while providing coverage of practical implementation (coding) issues. The field of Computer Science (CS) supports a multitude of essential technologies in science, engineering, and communication as a social medium. The varied and interconnected nature of computer technology permeates countless career paths making CS a popular and growing major program. Mastery of the science behind Computer Science relies on an understanding of the theory of algorithms and data structures. These concepts underlie the fundamental tradeoffs that dictate performance in terms of speed, memory usage, and programming complexity that separate novice programmers from professional practitioners.

Название: The Handbook of Data Science and AI: Generate Value from Data with Machine Learning and Data Analytics
Автор: Stefan Papp, Wolfgang Weidinger, Katherine Munro, Bernhard Ortner, Annalisa Cadonna, Georg Langs, Roxane Licandro, Mario Meir-Huber
Издательство: Hanser Publications
Год: 2022
Страниц: 606
Язык: английский
Формат: epub (true)
Размер: 45.1 MB

Data Science, Big Data, and Artificial Intelligence (AI) are currently some of the most talked-about concepts in industry, government, and society, and yet also the most misunderstood. This book will clarify these concepts and provide you with practical knowledge to apply them. The book approaches the topic of Data Science from several sides. Crucially, it will show you how to build data platforms and apply Data Science tools and methods. Along the way, it will help you understand - and explain to various stakeholders - how to generate value from these techniques, such as applying Data Science to help organizations make faster decisions, reduce costs, and open up new markets. Furthermore, it will bring fundamental concepts related to Data Science to life, including statistics, mathematics, and legal considerations. There had been a dispute over whether R or Python was the primary language for data scientists. While R is popular within special user groups, especially academia, the industry seems to favor Python. As a result, Python may have become the lingua franca in this domain. Moreover, Python engineers have tons of analytical frameworks available to them, such as Keras, PyTorch, Scifi, NumPy, and many more.

Название: Engineering Signal Analysis: From Fourier to filtering: Exercises
Автор: Max Mulder, Rowenna Wijlens, Christian Tiberius
Издательство: Delft University of Technology
Год: 2026
Страниц: 251
Язык: английский
Формат: pdf (true), epub
Размер: 10.1 MB

This book, Exercises, contains hundreds of exercises, including answers and worked examples, for studying and practicing the theory. Python scripts illustrate how to perform spectral signal analysis on a computer. The companion book, Theory, is an introductory textbook on the analysis of signals in time and frequency. It takes an engineer’s perspective and discusses how to characterize, analyze and operate on signals. The basic theoretical concepts, Fourier series and transform, are explained in continuous time. It then introduces discrete-time signals, addressing how sampling and finite signal duration affect spectral analysis. It discusses the discrete Fourier transform and its use in spectral estimation. The Theory book concludes with an introduction to linear systems and signal filtering. This book contains many exercises, ranging from completing small theoretical proofs, performing derivations, working out numerical calculation problems to doing computer-based assignments with Python.

Название: Ultimate Java Design Patterns: Master Creational, Structural, Behavioral, Concurrency, and Architectural Patterns for Scalable Enterprise Java Applications
Автор: Ricken Bazolo
Издательство: Orange Education Pvt Ltd, AVA
Год: 2026
Страниц: 317
Язык: английский
Формат: epub (true)
Размер: 38.1 MB

Think Like an Architect. Code Like a Master. Design patterns are the shared language of great software engineering — and mastering them is what separates Java developers who write code from architects who build systems. Ultimate Java Design Patterns gives you a comprehensive, practical command of every major pattern category, from Foundational Creational, Structural, and Behavioral patterns to Concurrency, Architectural, and emerging AI-driven design approaches. You begin with core pattern principles and their Java implementations, then progressively advance through real-world applications covering distributed systems, microservices, security, and cloud-native development. Every pattern is grounded in clear, practical Java examples with hands-on exercises that show not just how patterns work, but when and why to apply them in production systems. The final section addresses testing and debugging with patterns, framework-level pattern integration, and future trends including AI-driven Java architecture. Thus, by the end of the book, you can apply design patterns with confidence across any Java project, building systems that are clean, maintainable, and engineered to scale.