• Regeln für den Dokumente-Bereich:

    In den Börsenbereich gehören nur Angebote die bereits den Allgemeinen Regeln entsprechen.

    Allgemeines:

    Nicht erlaubt im Dokumente-Bereich sind:

    - indizierte Titel (inkl. Comics)
    - extremistische Werke, Zeitschriften und Comics (egal, welche Richtung)
    - jegliche Art von Pornographie
    - Anleitungen zu kriminellen Handlungen, gleich welcher Art
    - sadistische, menschenverachtende oder ähnliche Werke

    Nutzt den "Bedanken"-Button, bei Sammelthreads führen jegliche Kommentare, positiv wie negativ, sehr schnell zu einer Unübersichtlichkeit des Threads. Downmeldungen sind an den Uploader zu richten

    Vor dem Einstellen zu beachten:

    - Suchfunktion

    Vergewissert euch, dass es euer Dokument noch nicht im Board gibt, Doppelposts werden kommentarlos gelöscht. Ist es schon vorhanden, tragt es als Mirror im bestehenden Post ein.

    - Threadtitel

    Idealerweise ist sofort zu erkennen um was es sich handelt. Verseht euren Titel mit den relevanten Informationen, das hilft euch und damit auch uns und allen Suchenden erheblich weiter.

    Beispiel: [Thriller] Dan Brown - Inferno oder bei Magazinen:

    Computerbild - 14/2014 (es muss ersichtlich sein, um welche Ausgabe und welches Magazin es sich handelt)

    Folgende Präfixe stehen im Unterforum "Unterhaltung" zur Verfügung:

    [Humor]
    [Drama]
    [Erotik]
    [Fantasy]
    [Krimi]
    [Roman]
    [Thriller]
    [Horror]
    [Science Fiction]

    Inhalt des Beitrags:

    Folgende Pflichtangaben gilt es einzuhalten:

    - Autor
    - Titel
    - Präfix
    - Cover
    - Genre
    - Inhaltsbeschreibung
    - enthaltene Formate
    - Gesamtgröße des Downloads
    - Hoster
    - ggf. Passwort

    Nicht erlaubt sind alle Dateien, die den Download unnötig aufblähen um eine Affiliategrenze zu erreichen, wie zB. mp3-files, übergroße Bilder, etc.

    Ebenso nicht erlaubt sind sämtliche Dateien mit DRM, persönlichen Daten, etc., diese werden kommentarlos zu eurem eigenem Schutz gelöscht.

    Achtet bitte bei der Konvertierung der Formate auf die Lesbarkeit, ein epub, was nur einfach durch Calibre gejagt wird um ein PDF zu erhalten, ist zu 99% eben nicht lesbar. Wenn ihr es nicht könnt, dann lasst es besser oder lest euch ein, wie man es richtig macht.


    Unterforum Comics:

    Threadtitel:

    Ähnlich, wie bei Unterhaltung und Magazinen, sollte der Titel alle relevanten Informationen enthalten, hier bitte

    - den Titel des Comics
    - den Verlag (einige Comics sind in verschiedenen Verlagen erschienen)
    - das Erscheinungsjahr

    Erlaubt sind folgende Formate:

    - CBR
    - CBZ

    Grundsätzlich gilt: jede Version eines Comics erhält einen eigenen Thread, Ersteller eines Comics können ihre Bände gerne mit dem Zusatz (Original-Release) versehen.

    Bei Unsicherheiten zur korrekten Benennung bitte die Informationen von www.comicguide.de nutzen.

    Inhalt des Beitrags:

    Pflichtangaben hier sind:

    - Titel des Bandes und ggf. Nummer
    - Cover
    - falls bekannt technische Daten (DPI, Breite, Speicherqualität)
    - Größe des Downloads
    - Hoster
    - ggf. Passwort
    - falls bekannt Releasenamen
  • Bitte registriere dich zunächst um Beiträge zu verfassen und externe Links aufzurufen.

++ Premium IPTV ++ 7000 Live Sender ++ UHD Qualität ++ Mediathek mit 18.000 Inhalten ++


VenneTV


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Data Structures and Algorithms for Beginners
English | 2024 | ISBN: 2940179945109 | Pages: 95 | EPUB (True) | 489.71 KB
Embark on a transformative journey into the heart of problem-solving with "Data Structures and Algorithms for Beginners." Tailored for beginners, this comprehensive guide unravels the complexities of data structures and algorithms, turning what may seem daunting into an exciting exploration of logical thinking and efficient computation.

In the opening chapters, readers are gently introduced to the fundamental concepts, laying a solid foundation for the exciting adventure ahead. What are data structures, and why do algorithms matter? The book answers these questions and more, making the seemingly abstract world of computer science tangible and accessible.
Explore the core data structures such as arrays, linked lists, trees, and graphs, and grasp the essence of algorithmic paradigms like divide and conquer, greedy algorithms, and dynamic programming. The journey continues with practical applications, from searching and sorting to graph algorithms, offering readers a real-world perspective on how these concepts are utilized in solving everyday problems.
The book is not just a theoretical guide; it's a hands-on experience. With clear explanations, pseudocode, and flowcharts, readers will be empowered to tackle problems with confidence. Dive into case studies, examine problem-solving strategies, and discover the art of breaking down complex issues into manageable parts.
"Data Structures and Algorithms for Beginners" doesn't stop at the basics. Advanced topics like hashing, trie data structures, and complexity analysis are unveiled, giving readers a glimpse into the depth and breadth of the field. The journey concludes with invaluable tips for interview preparation, ensuring that readers are well-equipped to showcase their newfound knowledge in a professional setting.
Let the pages guide you through the maze of data structures and algorithms, transforming challenges into triumphs. Unlock the power of logical thinking and efficient problem-solving with "Data Structures and Algorithms for Beginners." Your journey begins now.




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Data Structures And Algorithms Made Easy: Data Structures And Algorithmic Puzzles
English | 2023 | ASIN: B0CBW278NC | Pages not found | PDF | 13.82 MB
"Data Structures And Algorithms Made Easy: Data Structures and Algorithmic Puzzles" is a book that offers solutions to complex data structures and algorithms. It can be used as a reference manual by those readers in the computer science industry. This book serves as guide to prepare for interviews, exams, and campus work. In short, this book offers solutions to various complex data structures and algorithmic problems.

Topics Covered:
Introduction
Recursion and Backtracking
Linked Lists
Stacks
Queues
Trees
Priority Queue and Heaps
Disjoint Sets ADT
Graph Algorithms
Sorting
Searching
Selection Algorithms [Medians]
Symbol Tables
Hashing
String Algorithms
Algorithms Design Techniques
Greedy Algorithms
Divide and Conquer Algorithms
Dynamic Programming
Complexity Classes
Miscellaneous Concepts




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Data Structures and Algorithms with Python
English | 2024 | ISBN: 2940180480200 | Pages: 120 | EPUB (True) | 342.85 KB
Dive into the world of data structures and algorithms with this comprehensive guide tailored for Python programmers. "Data Structures and Algorithms with Python: Elevating Your Coding Skills with Data Structures and Algorithms" is an essential resource for anyone looking to deepen their understanding of computational methods and enhance their problem-solving skills.

Starting with the basics of Python and progressing through to complex data structures and algorithmic techniques, this book offers a structured approach to learning. It not only demystifies the theoretical aspects of the topics but also provides practical implementations and real-world applications, ensuring that readers gain hands-on experience.
Key Features:
Comprehensive Coverage:
From basic data types and control structures in Python to advanced topics like graph algorithms and dynamic programming, this book covers a wide range of fundamental and complex concepts.
Hands-On Learning:
Each chapter includes Python code examples, exercises, and challenges that encourage active participation and reinforce learning.
Complexity Analysis:
Understand how to evaluate the efficiency of algorithms and data structures using Big O notation, enabling you to select the most appropriate tool for your coding projects.
Real-World Applications:
Discover how data structures and algorithms are applied in various fields such as web development, data analysis, machine learning, and more, through case studies and projects.
Resources for Further Learning:
An extensive list of resources, including books, online courses, and tutorials, is provided to support continued learning and exploration beyond the book.
"Data Structures and Algorithms with Python" is more than just a book; it's a pathway to enhancing your coding expertise, improving your analytical thinking, and solving complex computational problems with confidence. Embark on this educational journey to unlock new possibilities in your programming career or hobbyist endeavors.




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Data Structures in Python
English | 2024 | ISBN: 2940180692948 | Pages: 120 | EPUB (True) | 463.05 KB
Unlock the power of Python with

"Data Structures in Python,"
a comprehensive guide designed for both beginners and experienced programmers. This book provides a clear and engaging exploration of data structures, offering you the tools and techniques to implement them effectively in real-world applications.
From fundamental concepts like lists, tuples, and dictionaries to more advanced structures such as trees, graphs, and hash tables, this guide breaks down complex topics into easily digestible sections. Each chapter features practical examples, hands-on exercises, and illustrative diagrams to reinforce your understanding and help you apply what you've learned.
In addition to covering essential data structures, this book emphasizes best practices for choosing the right structure for specific problems, optimizing performance, and enhancing your algorithms. You'll discover how to analyze time and space complexity, ensuring your code is efficient and scalable.
"Data Structures in Python"
serves as your go-to resource. Join the journey of mastering data structures, and empower yourself to tackle real-world challenges with confidence and creativity.




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Data Warehouse Essentials: Mastering the Foundations of Data Management
English | 2025 | ISBN: B0F2N4QL5J | Pages: 196 | EPUB (True) | 1.44 MB
Data Warehouse Essentials is a comprehensive course designed to empower individuals with a robust understanding of data warehousing concepts, architecture, and best practices. Whether you're an aspiring data professional or looking to improve your data management skills, this course provides the essential knowledge needed to design, implement, and optimize a data warehouse effectively.

Master the Fundamentals of Data Warehousing Understand core data warehousing concepts and their importance in modern data management. Gain insights into key architectural components and design considerations. Learn data modeling techniques, including ER models and star schemas. Explore the essentials of ETL processes and integrating multiple data sources. Discover popular data warehousing tools and technologies. Develop skills for querying, reporting, and optimizing data warehouse performance. Ensure security, compliance, and governance in data warehousing. Identify the relationship between big data and data warehouses.
Comprehensive Guide to Data Warehousing Concepts and Techniques
This course begins with an introduction to data warehousing, providing an overview of its fundamental concepts, highlighting the significant impact they have in today's data-driven decision-making processes. Students will delve into the architecture of data warehouses, examining key components and the various design considerations crucial for creating efficient systems.
As learners progress, they will explore data modeling techniques, including Entity-Relationship (ER) models and star schemas, which are integral for organizing and structuring data within a warehouse. The course further covers essential ETL (Extract, Transform, Load) procedures necessary for data integration and cleansing, ensuring a smooth and accurate data flow into the warehouse.
The practical skills taught extend to the use of popular data warehousing tools and technologies, aiding students in navigating the current technology landscape. Additionally, the course addresses the critical areas of querying and reporting, providing techniques for effective data analysis and visualization.
Individuals will gain insights into performance optimization strategies, essential for maintaining the efficiency and speed of data warehouse operations. Furthermore, the course emphasizes security and data governance, critical for ensuring that data warehouses meet compliance requirements and remain secure.




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Data-Driven Cybersecurity (MEAP V05) by Mariano Mattei
English | 2025 | ISBN: 9781633436107 | 470 pages | PDF,EPUB | 24.62 MB
Measure, improve, and communicate the value of your security program.

Every business decision should be driven by data-and cyber security is no exception. In Data-Driven Cybersecurity, you'll master the art and science of quantifiable cybersecurity, learning to harness data for enhanced threat detection, response, and mitigation. You'll turn raw data into meaningful intelligence, better evaluate the performance of your security teams, and proactively address the vulnerabilities revealed by the numbers.
Data-Driven Cybersecurity will teach you how to:
Align a metrics program with organizational goals
Design real-time threat detection dashboards
Predictive cybersecurity using AI and machine learning
Data-driven incident response
Apply the ATLAS methodology to reduce alert fatigue
Create compelling metric visualizations
Data-Driven Cybersecurity teaches you to implement effective, data-driven cybersecurity practices-including utilizing AI and machine learning for detection and prediction. Throughout, the book presents security as a core part of organizational strategy, helping you align cyber security with broader business objectives. If you're a CISO or security manager, you'll find the methods for communicating metrics to non-technical stakeholders invaluable.
about the book
Data-Driven Cybersecurity shows you the metrics, data, and KPIs that will help you assess and enhance the performance of your cyber security programs. You'll learn how to turn complex metrics into actionable security practices, following the unique ATLAS (Alert Threshold Lifecycle Assessment System) methodology created by author Mariano Mattei. You'll go hands-on to build a real-time threat detection dashboard, and discover how AI and machine learning can proactively predict cybersecurity incidents. Case studies, interactive exercises, templates for KPIs, and expert insights help illustrate each new concept.




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Data-Driven Decision Support System in Intelligent HealthCare
by Bhattacharyya, Debnath;Hu, Yu-Chen;, Yu-Chen Hu
English | 2025 | ISBN: 1032806273 | 272 pages | True EPUB | 11.73 MB

Machine Intelligence with Generative AI is one of the most trending topics with applications in almost all fields of life. In healthcare, it is not only accelerating the development of new products, but also automating the generation of new and synthetic content making it easier to train and improve machine learning models. Some of the biggest achievements of Generative AI in healthcare have been drug discovery, personalized care, differentially private synthetic data generation, operational efficiency, and many more. Generative AI models like Generative Adversarial Networks, and Variational Autoencoders are employed to generate synthetic medical images, aiding in data augmentation, facilitating disease diagnosis, and enabling advanced medical imaging research. Additionally, Generative AI techniques are being utilized for creating realistic electronic health records (EHRs) and simulated patient data, supporting privacy-preserving data sharing, and empowering innovative studies for personalized medicine and drug development. NLP models like ClinicalBERT use transformer-based deep learning architecture to understand and represent contextual information in large clinical text datasets, such as electronic health records (EHRs) and medical literature, and can better grasp medical terminologies, domain-specific language, and contextual nuances that are unique to the healthcare field. This volume delves into the realm of Machine Intelligence with Generative AI and explores its impact on the healthcare industry.Generative AI is one of the most trending topics and application in every field of Science and Engineering with AI and Machine Intelligence. It is used to develop new products and automate the system by generating the new and improved models and improve decision making systems.






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Data-Intensive Applications: Design, Development, and Deployment Strategies for Scalable and Reliable Systems
English | 2024 | ISBN: 2940179805403 | Pages: 120 | EPUB (True) | 538.00 KB
"Data-Intensive Applications: Design, Development, and Deployment Strategies for Scalable and Reliable Systems" is a comprehensive guide to building robust and scalable applications in the era of big data. With the explosion of data in recent years, building applications that can handle massive amounts of data has become increasingly important. This book covers the entire lifecycle of data-intensive applications, from designing and developing the application to deploying it in a production environment.

The book begins with an introduction to the challenges and opportunities of building data-intensive applications. It then moves on to cover the key concepts and technologies used in building these applications, including distributed systems, data processing frameworks, and storage technologies. The book also covers best practices for designing and developing data-intensive applications, including how to handle data at scale, how to ensure reliability and fault tolerance, and how to optimize performance.
In addition, the book covers the deployment and management of data-intensive applications, including strategies for deploying applications in the cloud, managing infrastructure, and monitoring and debugging applications in production. The book also includes case studies and real-world examples from companies that have successfully built and deployed data-intensive applications.
Whether you are a software engineer, data scientist, or IT professional, this book will provide you with the knowledge and skills you need to build and deploy data-intensive applications that are scalable, reliable, and performant.




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Data-Oriented Design for Games (MEAP V04) by Nitzan Wilnai
English | 2025 | ISBN: 9781633435612 | 287 pages | PDF,EPUB | 24.78 MB
Use Data-Oriented Design to deliver games with outstanding performance while using less time and resources.

Data-Oriented Design (DOD) has become standard practice for AAA games and indie devs who need to squeeze every drop of performance out of hardware and deliver games on a rapid schedule. DOD is a programming practice that streamlines the way your code accesses, stores, and uses data, taking advantage of modern CPU architecture and accelerating the dev process. Data-Oriented Design for Games is a unique and comprehensive guide to architecting and coding games using DOD principles.
In Data-Oriented Design for Games you'll learn:
Data-Oriented Design and its application to game development
Optimize performance on modern CPU architecture
Reduce complexity by separating data from logic
Improve code extensibility through data-first problem solving
The Entity Component System (ECS) and its relationship to DOD
Implement DOD in Unity and other object-oriented engines
Modern games need to be smooth, high-framerate experiences with deep gameplay that keeps users hooked for years. Data-oriented design takes advantage of modern CPUs to upgrade game performance, easily outpacing traditional object-oriented programming. DOD uses arrays instead of objects, avoids design patterns and subroutines, and utilizes pure atomic functions as much as possible. Plus, because you're only thinking about data and logic, DOD-games take less manpower and time than building with OOP. Data-Oriented Design for Games reveals how you can bring this powerful programming approach to your own projects. You'll discover both the essential theory behind DOD, and put it into practice to develop a complete game project.
about the book
Data-Oriented Design for Games teaches you to deliver high-performance games, with code that's simpler to extend and maintain. You'll learn to design games from scratch using DOD and also how to apply DOD to existing object-oriented codebases. Through a simulated development process-complete with Jira tickets-you'll construct a complete "survivor" style game that runs at a high framerate on limited hardware while being easy to expand. The book is fully illustrated with Unity architectural examples, diagrams, and engaging war stories from author Nitzan Wilnai's 20+ year career, punctuated by helpful sidebars that dispel DOD myths.




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Database and Framework project in Python: build modern web applications with a Python framework
English | 2023 | ASIN: B0C2C5FN7H | 372 pages | Epub | 3.38 MB
Python is a popular and influential high-level programming language widely used by beginners and professionals. It is known for its simplicity and readability, making it an ideal language for those just starting to learn to program.

In this book you will learn:
1. Digging Deeper Into Django Migrations
2. Use Redis With Python
3. Create an Index in Django Without Downtime
4. Django Migrations
5. Efficient Caching in Distributed Applications
6. Building a Simple Web App
7. Getting Started with Django Channels
8. Caching in Django With Redis
9. AWS Elastic Beanstalk
10. A Web Service Application Comparison
11. Fun with Django's New Postgres Features
12. Deploying a Django
13. Web Scraping with Scrapy and MongoDB
14. Web Scraping and Crawling
15. Handling Email Confirmation During Registration
16. Implementing a Redis Task Queue
17. Setting up Postgres, SQLAlchemy, and Alembic
18. A Simple Todo List Powered by Flask and RethinkDB
19. Migrating from SQLite to MySQL
20. Introduction to Python SQL Libraries
Overall, Python is an excellent choice for anyone who wants to learn programming, whether you're interested in web development, data analysis or want to learn a new skill. With its simplicity, readability, and versatility, Python is an excellent language to start your programming journey.




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Database Design with SQL: Building Fast and Reliable Systems
English | 2024 | ISBN: B0DL3ZZC2S | Pages: 425 | EPUB (True) | 494.60 KB
"Database Design with SQL: Building Fast and Reliable Systems" is an essential resource for beginners eager to master the fundamentals of database management and SQL. This comprehensive guide demystifies the core principles of database systems, providing readers with the knowledge to design efficient data architectures and execute complex SQL operations. Covering everything from basic data structures to advanced query optimization, the book equips learners with the crucial skills needed to build and manipulate robust databases that meet modern demands.

The book delves into the intricacies of relational databases and normalization, offering practical insights into data modeling and schema design. Readers will explore the power of SQL in both data retrieval and manipulation, progressing through foundational commands to sophisticated techniques like dynamic SQL and window functions. Additionally, the text addresses critical aspects of database security, transactions, and concurrency control, ensuring that systems remain resilient and secure in multi-user environments.
Beyond relational databases, "Database Design with SQL" introduces the versatile world of NoSQL and its role in big data, enabling learners to handle diverse data types and high-volume datasets. Through real-world case studies and best practices for database administration, this guide offers valuable strategies for maintaining performance and reliability. Whether you are embarking on a career in database management or seeking to enhance your technical expertise, this book is your gateway to mastering database design and SQL with confidence.




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Databricks Certified Data Engineer Associate Study Guide: In-Depth Guidance and Practice
English | 2025 | ISBN: 1098166833 | 408 pages | PDF | 25.51 MB
Data engineers proficient in Databricks are currently in high demand. As organizations gather more data than ever before, skilled data engineers on platforms like Databricks become critical to business success. The Databricks Data Engineer Associate certification is proof that you have a complete understanding of the Databricks platform and its capabilities, as well as the essential skills to effectively execute various data engineering tasks on the platform.

In this comprehensive study guide, you will build a strong foundation in all topics covered on the certification exam, including the Databricks Lakehouse and its tools and benefits. You'll also learn to develop ETL pipelines in both batch and streaming modes. Moreover, you'll discover how to orchestrate data workflows and design dashboards while maintaining data governance. Finally, you'll dive into the finer points of exactly what's on the exam and learn to prepare for it with mock tests.
Author Derar Alhussein teaches you not only the fundamental concepts but also provides hands-on exercises to reinforce your understanding. From setting up your Databricks workspace to deploying production pipelines, each chapter is carefully crafted to equip you with the skills needed to master the Databricks Platform. By the end of this book, you'll know everything you need to ace the Databricks Data Engineer Associate certification exam with flying colors, and start your career as a certified data engineer from Databricks!
You'll learn how to:
Use the Databricks Platform and Delta Lake effectively
Perform advanced ETL tasks using Apache Spark SQL
Design multi-hop architecture to process data incrementally
Build production pipelines using Delta Live Tables and Databricks Jobs
Implement data governance using Databricks SQL and Unity Catalog
Derar Alhussein is a senior data engineer with a master's degree in data mining. He has over a decade of hands-on experience in software and data projects, including large-scale projects on Databricks. He currently holds eight certifications from Databricks, showcasing his proficiency in the field. Derar is also an experienced instructor, with a proven track record of success in training thousands of data engineers, helping them to develop their skills and obtain professional certifications.




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