Data Science

This reference volume consists of revised, edited, cross-referenced, and thematically organized articles from Software Diagnostics Institute and Software Diagnostics Library (former Crash Dump Analysis blog) about software diagnostics, root cause analysis, debugging, crash and hang dump analysis, software trace and log analysis written in March - September 2016.

This reference volume consists of revised, edited, cross-referenced, and thematically organized articles from Software Diagnostics Institute and Software Diagnostics Library (former Crash Dump Analysis blog) about software diagnostics, root cause analysis, debugging, crash and hang dump analysis, software trace and log analysis written in August 2015 - February 2016.

This reference volume consists of revised, edited, cross-referenced, and thematically organized articles from Software Diagnostics Institute and Software Diagnostics Library (former Crash Dump Analysis blog) about software diagnostics, debugging, crash dump analysis, memory forensics, software trace and log analysis written in December 2014 - July 2015.

This reference volume consists of revised, edited, cross-referenced, and thematically organized articles from Software Diagnostics Institute and Software Diagnostics Library (former Crash Dump Analysis blog) about software diagnostics, debugging, crash dump analysis, memory forensics, software trace and log analysis written in June 2014 - November 2014.

This reference volume consists of revised, edited, cross-referenced, and thematically organized articles from Software Diagnostics Institute and Software Diagnostics Library (former Crash Dump Analysis blog) about software diagnostics, debugging, crash dump analysis, software trace and log analysis, malware analysis and memory forensics written in November 2011 - May 2014.

Discover the full potential of Microsoft Excel in Hallo Microsoft Excel: Mastering Data Analytics. This book is packed with hands-on labs (HOL) designed to teach you how to transform raw data into meaningful insights. Learn how to connect Excel with SQL Server, configure queries, and load data seamlessly. Master data visualization with tools like PivotTables, Sparklines, and Maps. Dive into dynamic reports, dashboards, and what-if analysis to create interactive and visually compelling insights. Each exercise, from conditional formatting to growth analysis, is crafted to make you a data analytics expert using Excel. Perfect for beginners and professionals alike, this book is your guide to mastering data analytics, step by step!

This reference volume consists of revised, edited, cross-referenced, and thematically organized articles from Software Diagnostics Institute and Software Diagnostics Library (former Crash Dump Analysis blog) about memory dump analysis, software trace and log analysis, software troubleshooting, and debugging written in November 2010 - October 2011.

"How Does Computer Science Work?" answers 28 key questions every software engineer should know, unraveling the technologies that shape our digital world. From how browsers work and cryptography secures data to AI, Web3, and quantum computing, this book bridges curiosity and understanding. Perfect for students, self-taught programmers, and seasoned developers, it’s your ultimate guide to mastering foundational concepts and cutting-edge innovations in computer science.

Digital Sustainability: From Principles to Practice shows how digital technologies shape our environmental and societal future, and how we can design them responsibly. It equips students and professionals with concrete tools to build more sustainable software, systems, and digital solutions. Less theory for its own sake, more competence for the reality we’re about to enter.

This book provides a practical guide to critical data science methods, focusing on their application in credit risk management. Using examples in R and Python, it presents step-by-step processes for applying various analytical techniques while highlighting the importance of aligning methods with the specific characteristics of the data. Designed for practitioners and those with foundational data science and banking knowledge, the book bridges theory and practice with real-world examples.

Unlock your SQL skills with "Self-Guided SQL: Build Your SQL Skills with SQLite"! This comprehensive book is designed for both the classroom and self-driven learners who value practice and hands-on experience. Through progressive challenges and repeated exercises, this guide helps you build a solid foundation in SQL using the powerful and popular SQLite database software. With "Self-Guided SQL", you will learn by doing, seeing SQL in action with enough explanation to help you understand what's happening behind the scenes. Every lesson moves you forward and builds on the skills you've previously gained, helping to continually reinforce them. "Self-Guided SQL" will help you take control of your your own education in these versatile and powerful technologies, ensuring that you not only understand SQL concepts but can also apply them confidently and effectively!

In an era where AI's potential is clear but its path isn't, "Enterprise AI: Strategic Blueprint for Purple People" offers a compass for decision-makers. Uncover the strategic framework that aligns AI with your organization's vision and propels you toward a future of informed innovation.

Master the art of data engineering with Enterprise Big Data Engineer: Fundamental Approaches for Data Engineering and the Creation of Data Pipelines. This comprehensive guide dives deep into the essential skills and strategies needed to design, build, and manage scalable data systems in today's complex enterprise environments. Explore advanced techniques for batch and stream processing, develop secure and reliable data pipelines, and ensure your data's quality, security, and governance. As the official guide for the Enterprise Big Data Engineer (EBDE) certification by APMG International, this book is your ultimate resource for achieving professional excellence and propelling your career forward in the dynamic field of data engineering.

Unlock the power of linear algebra in your data science projects! "Linear Algebra Essentials for Data Scientists" dives into the key concepts driving data analysis and machine learning. With clear explanations, practical Python examples, and hands-on exercises, this book is your gateway to mastering the mathematical foundations of data science.

The book was designed to introduce NumPy features in a structured way, with each chapter building on your knowledge incrementally. Revised and updated for NymPy 2.