• 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.

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Collection Download Ebooks Best Seller Updated Daily

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Data Science for Web3: A comprehensive guide to decoding blockchain data with data analysis basics and machine learning cases
English | 2023 | ISBN: B0C6QQBLZ8 | Pages: 555 | EPUB (True) | 7.72 MB
Data is the new oil and Web3 is generating it at an unprecedented rate. Complete with practical examples, detailed explanations, and ideas for portfolio development, this comprehensive book serves as a step-by-step guide covering the industry best practices, tools, and resources needed to easily navigate the world of data in Web3.

You'll begin by acquiring a solid understanding of key blockchain concepts and the fundamental data science tools essential for Web3 projects. The subsequent chapters will help you explore the main data sources that can help address industry challenges, decode smart contracts, and build DeFi- and NFT-specific datasets. You'll then tackle the complexities of feature engineering specific to blockchain data and familiarize yourself with diverse machine learning use cases that leverage Web3 data.
The book includes interviews with industry leaders providing insights into their professional journeys to drive innovation in the Web 3 environment. Equipped with experience in handling crypto data, you'll be able to demonstrate your skills in job interviews, academic pursuits, or when engaging potential clients.
By the end of this book, you'll have the essential tools to undertake end-to-end data science projects utilizing blockchain data, empowering you to help shape the next-generation internet.





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Data Science: Foundations and Hands-on Experience:
Handling Economic, Spatial, and Multidimensional Data with R

English | 2025 | ISBN: 9819646820 | 650 Pages | PDF EPUB (True) | 67 MB

This book will take readers from foundational concepts to practical applications, enabling them to transform raw data into meaningful insights. It covers key skills such as data collection, cleaning, organization, exploration, analysis, and impactful presentation-core competencies for navigating today's data-rich landscape.





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Data Science in 30 Days: The Complete Beginner's Guide
English | 2025 | ISBN: B0DXBD67RD | Pages: 179 | Epub | 4.01 MB
Data Science in 30 Days: The Complete Beginner's Guide is the ultimate hands-on roadmap for anyone looking to master data science for dummies and transition into the world of data-driven decision-making. Designed to take you from an absolute beginner to a confident data practitioner in just 30 days, this book provides a structured, easy-to-follow approach to learning data science for beginners efficiently.

With step-by-step lessons, real-world examples, and hands-on exercises, this book is perfect for those looking for a Python data science book that balances theory with practical applications. Whether you are a student, professional, or hobbyist, you'll find everything you need to get started with data science projects with Python and apply it in various domains such as business analytics, finance, artificial intelligence, and big data processing.
What You'll Learn in 30 Days:
✔ The fundamentals of data science, including data collection, cleaning, and preprocessing
✔ How to use Python, NumPy, Pandas, and MatDescriptionlib for Python for data science tasks
✔ Exploratory data analysis (EDA) techniques to uncover insights from data
✔ Introduction to statistics, probability, and hypothesis testing for data science for business applications
✔ Supervised and unsupervised machine learning models, including regression, classification, and clustering
✔ Working with databases, SQL queries, and big data tools like Apache Spark
✔ Advanced topics such as data science for finance, deep learning, NLP, time series analysis, and model deployment
Why This Book Stands Out:
✔ A structured day-by-day learning plan to keep you on track
✔ Practical exercises and coding challenges to reinforce each concept
✔ Covers both beginner and intermediate topics, making it ideal for continuous learning
✔ A bonus section with cheat sheets, common errors, and interview questions
If you're looking for the best Python data science book that breaks down complex concepts into digestible lessons, this book is for you. Whether you're interested in data science projects with Python, preparing for a data science bootcamp, or simply want to explore data science for business in an easy-to-understand manner, this book provides a complete, practical guide.





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Data Science in Healthcare
English | 2024 | ISBN: 2940180745613 | Pages: 165 | EPUB (True) | 377.30 KB
In an era where data is the lifeblood of progress, healthcare is not untouched by the wave of transformation brought by data science. "Data Science in Healthcare: Transforming the Future of Medicine" delves deep into this revolution, illuminating the profound impact data science is having on the healthcare landscape.

Healthcare, a field built on the foundations of compassion and expertise, is embracing the power of data and artificial intelligence to enhance patient care, streamline operations, and push the boundaries of medical research. This book is your comprehensive guide to understanding and navigating the ever-expanding world of data science in healthcare.
From the fundamental principles of data collection, preprocessing, and exploratory data analysis, to advanced techniques in machine learning, deep learning, and natural language processing, this book equips you with the knowledge and tools needed to harness the potential of healthcare data. You will explore the integration of data science with electronic health records, medical imaging, and telemedicine, and gain insights into the ethical and legal considerations that govern the use of healthcare data.
With real-world case studies and success stories, you will witness the practical applications of data science in disease diagnosis, personalized medicine, drug discovery, and beyond. Whether you are a healthcare professional seeking to optimize patient outcomes or a data scientist eager to make a difference in the field of medicine, this book provides the essential knowledge to bridge the gap.
"Data Science in Healthcare" doesn't just dwell on the present; it looks to the future of healthcare, from AI-driven innovations to the challenges that lie ahead. It offers a roadmap to navigate the dynamic landscape, ensuring you are prepared for the exciting possibilities and the ethical responsibilities that come with them.
As healthcare evolves into a data-driven industry, this book is your essential companion, providing the insights and wisdom to leverage the power of data science for the well-being of individuals and society. Discover how data science is transforming healthcare and get ready to be a part of the journey to a healthier, more connected world.





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Data Science Unveiled: Navigating the Future with Analytical Precision
English | 2025 | ASIN: B0DX7HRKVW | 296 Pages | Epub | 521.84 KB
"Data Science Unveiled: Navigating the Future with Analytical Precision" is a comprehensive guide that explores the fundamentals and advanced concepts of data science, offering practical insights for both beginners and experienced practitioners. This book covers 20 detailed chapters that progress from basic principles to cutting-edge developments in the field.

Readers will learn about:
Core concepts and methodologies in data science
Essential tools and technologies, including Python, R, and SQL
Advanced topics like machine learning, deep learning, and natural language processing
Big data analytics and cloud computing solutions
Data visualization techniques and best practices
Ethical considerations and governance in data science
Building a professional portfolio and career development
The book combines theoretical knowledge with practical applications, featuring real-world examples and detailed explanations of complex concepts. It addresses current trends and future developments, including the role of AI, quantum computing, and automation in shaping the future of data science.
Whether you're a student, professional, or business leader, this book provides valuable insights into harnessing the power of data science for better decision-making and innovation. Written in an accessible style while maintaining technical rigor, it serves as both a learning resource and a reference guide for navigating the evolving landscape of data science.
Ideal for:
Data science students and practitioners
Business analysts and decision-makers
IT professionals transitioning to data science
Anyone interested in understanding the impact of data science on modern business and society
This comprehensive guide empowers readers to understand, implement, and leverage data science techniques in their professional endeavors, preparing them for a future driven by data-based insights and decisions.





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Data Science with Julia (The Language of Data Science)
English | 2025 | ISBN: B0F2Z7D3CB | Pages: 623 | PDF | 673.29 KB
Reactive Publishing

Data Science with Julia
By Hayden Van Der Post
Experience data science reimagined-faster, leaner, and more elegant-with the Julia programming language.
While Python and R have dominated the data science conversation for years, Julia is the breakthrough language designed from the ground up for high-performance numerical computing. Data Science with Julia is your hands-on guide to mastering the full data science pipeline using this modern, lightning-fast tool.
From data wrangling to modeling to visualization and deployment, this book equips you to:
Harness Julia's speed for massive datasets and real-time analytics
Perform advanced statistical analysis with native packages
Build machine learning models using Flux and MLJ.jl
Visualize data interactively with Makie and Descriptions.jl
Deploy Julia-based data apps and scripts in production workflows
Written for analysts, researchers, and developers tired of clunky workarounds and sluggish runtime, this is a pragmatic, performance-first approach to doing data science in the 2020s.





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Data Science with Python for Beginners
English | 2024 | ISBN: 2940180774347 | Pages: 120 | EPUB (True) | 405.98 KB
In this accessible and engaging book, you'll traverse the fundamentals of Python programming, seamlessly transitioning into the realm of data science. From setting up your Python environment to mastering essential libraries like NumPy, Pandas, and MatDescriptionlib, each chapter builds upon the last, providing a scaffolded approach to learning.

Explore the art of data wrangling with Pandas, gaining proficiency in cleaning, preprocessing, and merging datasets. Demystify the complexities of exploratory data analysis (EDA) and statistical concepts, empowering you to make informed decisions and draw valuable insights from your data.
Dive into the heart of machine learning, where you'll grasp the basics of model training, evaluation, and hyperparameter tuning using the powerful Scikit-Learn library. Discover the significance of feature engineering, delve into time series analysis, and unravel the potential of big data with Apache Spark and Dask.
As you progress, the book navigates through advanced tools for data visualization, such as Descriptionly and Dash, allowing you to create stunning and interactive visualizations that bring your data to life. Uncover the ethical considerations in data science, addressing bias, privacy, and security, and cap off your journey with real-world projects and case studies, cementing your newfound skills.
"Data Science with Python for Beginners" is not just a book; it's your companion in the evolving landscape of data science. Packed with practical examples, exercises, and hands-on projects, this guide instills confidence in beginners and ignites a passion for data exploration and analysis. Whether you aspire to make data-driven decisions or embark on a career in data science, this book is your key to unlocking the doors of insight and innovation. Let Python be your guide as you unravel the vast possibilities of data science!





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Data Science with Python: From Zero to Machine Learning
English | 2025 | ISBN: 9798230222682 | Pages: 161 | EPUB (True) | 596.80 KB
Data Science with Python: From Zero to Machine Learning

?
Your Complete Guide to Mastering Data Science - No Experience Needed!
Want to break into the high-demand field of data science? This
all-in-one guide
takes you from
absolute beginner to machine learning pro
using Python - the #1 language for data science.
What You'll Learn:
✅
Python Basics → ML Mastery:
Start coding in Python and progress to
building/deploying ML models
✅
Key Libraries:
Master
NumPy, Pandas, MatDescriptionlib, Seaborn
for data analysis & visualization
✅
Real-World Data Wrangling:
Clean, preprocess, and analyze data like a pro
✅
Machine Learning Algorithms:
Regression, Classification, SVMs, Neural Networks & more
✅
Deep Learning:
Build AI models with
TensorFlow & Keras
✅
Model Deployment:
Learn to
put your models into production
✅
Ethics & Best Practices:
Responsible AI development
Perfect For:
✔ Aspiring data scientists
✔ Developers transitioning into AI/ML
✔ Analysts looking to upskill
✔ Anyone who wants a
job-ready data science portfolio
?
By the End, You'll Be Able To:
*
Analyze big datasets
with Python
*
Train ML models
that make predictions
*
Visualize insights
like a pro
*
Deploy solutions
that businesses use
?
Why This Book?
Zero to Advanced
- No prior experience needed
Hands-On Projects
- Learn by doing
Industry-Ready Skills
- Covers what employers want
Latest Tools
- Updated for the newest tools
Start Your Data Science Journey Today!





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Data Science with Python: Unlocking the Power of Pandas and Numpy
English | 2024 | ISBN: B0DL3QXBYP | Pages: 373 | EPUB (True) | 436.48 KB
"Data Science with Python: Unlocking the Power of Pandas and Numpy" is an essential guide for beginners and professionals alike, striving to master the art of data analysis using Python's robust ecosystem. This book delves into the foundational aspects of data science, providing readers with a comprehensive understanding of how to harness Python's capabilities for data manipulation and exploration. By covering key libraries such as Pandas and Numpy, it equips readers with the skills necessary to perform high-performance numerical computations and sophisticated data analysis tasks.

Structured to ensure a seamless learning experience, this book introduces essential Python programming concepts and progressively advances to more complex topics in data cleaning, preprocessing, and visualization. Each chapter is crafted to build upon the last, ensuring a coherent progression and a deepening of knowledge. With a series of practical projects, readers will gain hands-on experience in real-world data science applications, learning how to develop predictive models and deploy solutions effectively. Through this approach, the book bridges the gap between theoretical understanding and practical application, empowering readers to unlock the full potential of data science in today's data-driven landscape.





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Data Structures & Algorithms for AI: Building Smart Systems (AI from Scratch : Step-by-Step Guide to Mastering Artificial Intelligence Book 3)
English | 2025 | ASIN: B0DVSK4LTZ | 423 pages | Epub | 1.85 MB
AI from Scratch: Step-by-Step Guide to Mastering Artificial Intelligence (Book 3)

Artificial Intelligence (AI) is transforming industries, from healthcare to finance, robotics to real-time decision-making. But what makes AI models truly efficient? The answer lies in data structures and algorithms-the backbone of AI performance, scalability, and optimization.
Data Structures & Algorithms for AI: Building Smart Systems is a comprehensive guide designed to help AI engineers, machine learning practitioners, and software developers master the core computational techniques that power modern AI systems. As the third book in the AI from Scratch series, this volume takes a deep dive into the computational foundations necessary to build fast, scalable, and intelligent AI solutions.
What You'll Learn:
How arrays, linked lists, trees, graphs, and hash tables impact AI efficiency
Graph algorithms, reinforcement learning, and heuristic search for AI applications
Sorting, dynamic programming, and metaheuristics to optimize AI performance
Deep learning data structures, parallel computing, and real-time AI systems
AI-ready probabilistic data structures for handling large-scale and streaming data
Why This Book?
Unlike traditional algorithm books, which focus on generic applications, this book is tailored for AI professionals. You'll learn how to implement AI-driven data structures with a focus on speed, memory optimization, and scalability. From neural network optimizations to AI-powered search techniques, this book provides the computational toolkit needed for building high-performance AI applications.
Who Should Read This Book?
AI & Machine Learning Engineers optimizing model performance
Data Scientists looking for AI-focused algorithmic techniques
Software Developers implementing AI-based applications
Researchers & Students wanting a deep dive into AI-specific data structures
With real-world case studies, hands-on examples, and AI-specific optimizations, this book ensures that you don't just learn how data structures and algorithms work-but how to apply them to build smarter AI systems.





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Data Structures & Algorithms With Golang 101
English | 2024 | ASIN: B0DKTP6JMK | 280 pages | Epub | 226.71 KB
Why Data Structures and Algorithms?

Data structures and algorithms are the backbone of efficient problem-solving in computer science. They enable developers to organize, store, and manipulate data effectively, making applications faster, more scalable, and resource-efficient. From search engines to social media platforms, every modern technology leverages the power of DSA. Mastering DSA not only sharpens analytical thinking but also prepares developers to tackle complex challenges, making it a must-have skill for coding interviews and real-world projects.
Why Golang for DSA?
Golang, or Go, is a modern programming language known for its simplicity, performance, and efficiency. Designed by Google, Go excels in handling concurrent tasks, making it ideal for modern software solutions. Its clean syntax, built-in garbage collection, and robust standard library simplify complex implementations, including DSA. For beginners and professionals alike, Go provides a balanced learning curve and real-world applicability, making it a perfect language to explore DSA concepts.
About the Book
This book bridges the gap between theory and practice, combining foundational DSA concepts with practical Golang implementations. Each chapter offers clear explanations, hands-on examples, and real-world applications, ensuring a seamless learning experience. Whether you're preparing for interviews or building scalable systems, this book will empower you to solve problems with confidence and efficiency.
About the ✅Publisher
101 Book is a forward-thinking company dedicated to democratizing access to quality education by offering affordable learning materials. With a mission to empower learners globally, the company designs and distributes high-quality books, courses, and educational resources at exceptionally low prices. Focused on inclusivity and innovation, 101 Book ensures its products cater to diverse subjects, age groups, and learning needs. By leveraging cost-efficient production methods without compromising content quality, the company bridges the education gap, enabling millions to achieve academic success. Committed to excellence and accessibility, 101 Book is reshaping the landscape of affordable education, fostering knowledge for all.





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Data Structures and Algorithms for Beginners
English | 2024 | ISBN: 2940180884848 | Pages: 125 | EPUB (True) | 271.09 KB
Embark on your journey into the world of computing with "Data Structures and Algorithms for Beginners: A Beginner's Guide to Essential Concepts and Techniques." This book is expertly crafted to guide beginners through the fundamental principles that form the backbone of computer science. Whether you are a novice looking to delve into programming, a student preparing for your computer science courses, or a professional aiming to refresh your knowledge, this guide provides an essential foundation in data structures and algorithms.

"Data Structures and Algorithms for Beginners" demystifies complex topics with clear explanations, real-world examples, and practical exercises. Starting from the basics, you'll learn about different types of data structures, from simple arrays and linked lists to more intricate structures like trees and graphs. As you progress, you'll explore the mechanics and strategies of efficient algorithms, understanding how they manipulate and process data to solve problems.
This guide also dives into the critical aspect of algorithm analysis, teaching you how to evaluate the performance of an algorithm through concepts like time and space complexity. You'll gain hands-on experience with sorting and searching algorithms, discovering how they are applied in various applications and how they can be optimized for speed and efficiency.
Each chapter includes practical code examples in a beginner-friendly programming language, step-by-step walkthroughs, and illustrative diagrams to help solidify your understanding. By the end of this book, you will have a solid grasp of key concepts and be well-prepared to apply these techniques in practical scenarios, from software development to preparing for technical interviews.
Step into the world of computer science with confidence and curiosity! "Data Structures and Algorithms for Beginners" is your comprehensive guide to mastering these critical concepts, opening doors to a multitude of possibilities in technology and beyond.





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