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[booksz]

MindShifting: Stop Your Brain From Sabotaging Your Happiness and Success
English | 2025 | ISBN: 1952281814 | 237 Pages | EPUB | 7 MB
If you want to be motivated and persistent in overcoming obstacles, setbacks, and procrastination, those are mindsets. When you feel overwhelmed by obstacles, when setbacks make you want to quit or scream, when you can't seem to get started, those are mindsets as well.

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Miniband-Fitness: Das effektive Ganzkörper-Training
Deutsch | 2017 | ISBN: 3833862254 | 125 Pages | EPUB | 3 MB
Das Miniband - in der Handhabung total leicht und praktisch - ist ein Alleskönner in Sachen Fitness: Beim Krafttraining lassen sich damit die Muskeln von Kopf bis Fuß gezielt ansprechen. Und auch für das Herz-Kreislauf-Training mit Fettverbrennungsfaktor, das Stretching und die Koordination ist das Band vielseitig einsetzbar.

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Minimal Markdown for Authors: How to Write and Publish a Book Using Open Source Software
English | 2025 | ASIN: B0FJ6N5WMZ | 56 pages | EPUB (True) | 1.10 MB
This short book outlines the basic process I use when I am writing and publishing a new book. I use a combination of Markdown and conversion with Pandoc to create the files I need to publish on any platform I want to.

If you have just started writing a book and you know what you are writing but you don't know what software you should be using, this is a great book for you. There are other books that cover Markdown in more detail, but this book covers how to include headings, italics, bold, links, images, and how to convert your file into other formats using Pandoc. From there, it is possible to publish what you have written as a book or a website.
I made this book for my friends who know I have published many books but have questions about the process. It is easier than you might think but a book like this was not available back when I got started nor did I know what Markdown was back then. I could have saved so much time using Markdown to define my Chapters and other elements of my book. My hope is that this book will also save you time as you adapt my methods to what works for you.

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Mitochondria Recharged:
Reverse Fatigue, Supercharge Energy, and Slow Aging with the Science of Cellular Power
English | 2025 | ASIN : B0FBDSVMYG | 482 Pages | EPUB | 0.6 MB

This groundbreaking book reveals how modern science is reshaping everything we know about health, vitality, and disease prevention. From understanding how cellular energy is produced to learning how lifestyle changes can reignite your biological engine, this book empowers you to transform your health at the root level.

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Mobile Hacking: Break into Android & iOS Apps (Ethical)
English | 2025 | ASIN: B0F54FKDTT | 86 pages | PDF | 896.45 KB
Unlock the Secrets of Mobile Security!

In today's digital world, smartphones store our most sensitive data-from banking apps to private messages. But how secure are they really? "Mobile Hacking: Break into Android & iOS Apps" is the most comprehensive guide to ethical mobile penetration testing, teaching you how to find vulnerabilities before hackers do.
�� What You'll Learn:
✔ Android & iOS Reverse Engineering - Decompile apps, modify code, and bypass security checks.
✔ Real-World Exploits - Crack Wi-Fi networks, bypass biometric locks, and intercept traffic.
✔ Defensive Tactics - Secure your apps against hackers with proven techniques.
✔ Step-by-Step Labs - Hands-on exercises with tools like Frida, Burp Suite, and Kali NetHunter.
✔ Bonus Chapter - Hack Wi-Fi using only a mobile phone (no computer needed).
Who Is This Book For?
Ethical hackers & penetration testers
App developers who want to build secure software
IT students & cybersecurity enthusiasts
Anyone curious about mobile security
Why This Book Stands Out:
✅ No Fluff - Straight to practical techniques.
✅ Covers Both Android & iOS - Most books focus on just one.
✅ Legal & Ethical Focus - All methods are for authorized testing only.
Tools You'll Master:
Frida, Ghidra, APKTool, Objection
zANTI, Wireshark, Metasploit (Mobile Edition)
Checkra1n, Cydia, and more.
Disclaimer
⚠ WARNING: This book is for EDUCATIONAL PURPOSES ONLY.
The techniques described in this book are intended to help:
Security professionals improve defensive strategies.
Developers build more secure applications.
Students learn ethical hacking in controlled environments.
You must have explicit permission to test any system or network that you do not own. Unauthorized hacking is illegal and punishable by law. The author and ✅Publisher disclaim all liability for any misuse of this information.

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Model Context Protocol: Advanced AI Agents for Beginners
English | 2025 | ASIN : B0FCDCNJH8 | 161 Pages | EPUB | 19 MB
This book is for anyone who's ever looked at ChatGPT and thought, "Cool, but can it actually do stuff for me?" Like-not just chat. Actually take over tasks, run your software, automate your day.

That's where something called the Model Context Protocol (MCP) comes in. It's a lightweight system that lets AI take control of tools you already use-think Figma, Excel, WhatsApp, even Blender-without needing to write a single line of code.

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Modern Computer Vision with PyTorch: A practical roadmap from deep learning fundamentals to advanced applications and Generative AI
English | June 10, 2024 | ISBN: 1803231335 | 746 pages | EPUB (True) | 73.30 MB
The definitive computer vision book is back, featuring the latest neural network architectures and an exploration of foundation and diffusion models

Purchase of the print or Kindle book includes a free eBook in PDF format
Key Features
Understand the inner workings of various neural network architectures and their implementation, including image classification, object detection, segmentation, generative adversarial networks, transformers, and diffusion models
Build solutions for real-world computer vision problems using PyTorch
All the code files are available on GitHub and can be run on Google Colab
Book Description
Whether you are a beginner or are looking to progress in your computer vision career, this book guides you through the fundamentals of neural networks (NNs) and PyTorch and how to implement state-of-the-art architectures for real-world tasks.
The second edition of Modern Computer Vision with PyTorch is fully updated to explain and provide practical examples of the latest multimodal models, CLIP, and Stable Diffusion.
You'll discover best practices for working with images, tweaking hyperparameters, and moving models into production. As you progress, you'll implement various use cases for facial keypoint recognition, multi-object detection, segmentation, and human pose detection. This book provides a solid foundation in image generation as you explore different GAN architectures. You'll leverage transformer-based architectures like ViT, TrOCR, BLIP2, and LayoutLM to perform various real-world tasks and build a diffusion model from scratch. Additionally, you'll utilize foundation models' capabilities to perform zero-shot object detection and image segmentation. Finally, you'll learn best practices for deploying a model to production.
By the end of this deep learning book, you'll confidently leverage modern NN architectures to solve real-world computer vision problems.
What you will learn
Get to grips with various transformer-based architectures for computer vision, CLIP, Segment-Anything, and Stable Diffusion, and test their applications, such as in-painting and pose transfer
Combine CV with NLP to perform OCR, key-value extraction from document images, visual question-answering, and generative AI tasks
Implement multi-object detection and segmentation
Leverage foundation models to perform object detection and segmentation without any training data points
Learn best practices for moving a model to production
Who this book is for
This book is for beginners to PyTorch and intermediate-level machine learning practitioners who want to learn computer vision techniques using deep learning and PyTorch. It's useful for those just getting started with neural networks, as it will enable readers to learn from real-world use cases accompanied by notebooks on GitHub. Basic knowledge of the Python programming language and ML is all you need to get started with this book. For more experienced computer vision scientists, this book takes you through more advanced models in the latter part of the book.
Table of Contents
Artificial Neural Network Fundamentals
PyTorch Fundamentals
Building a Deep Neural Network with PyTorch
Introducing Convolutional Neural Networks
Transfer Learning for Image Classification
Practical Aspects of Image Classification
Basics of Object Detection
Advanced Object Detection
Image Segmentation
Applications of Object Detection and Segmentation
Autoencoders and Image Manipulation
Image Generation Using GANs

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Modern Django Web Development: With Channels, DRF, GraphQL, and React
English | 2025 | ASIN: B0F1XP6JPD | 441 Pages | PDF EPUB (True) | 15 MB
Django has evolved into a powerful full-stack framework ideal for developing data-driven web applications, continuously expanding with new tools for asynchronous solutions, APIs, and real-time applications. This book explores modern Django development best practices, including Django Channels for WebSockets, Django REST Framework (DRF) for REST APIs, Graphene and Strawberry for GraphQL APIs, and integrating a front-end built with React The content is structured into two main parts, covering both fundamental and advanced concepts in a practical and digestible manner.

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Modern Full-Stack React Projects: Build, maintain, and deploy modern web apps using MongoDB, Express, React, and Node.js
English | June 7, 2024 | ASIN: B0CY2MSDTC | 763 pages | EPUB (True) | 16.08 MB
Polish your web development skills by working on real-world projects for different use-cases of full-stack web development

Key Features
Understand how the different aspects of a MERN application come together through a series of practical projects
Set up frontend and backend projects that can be integrated and maintained together
Enhance your proficiency in building scalable and sustainable React projects
Purchase of the print or Kindle book includes a free PDF eBook
Book Description
Understanding full-stack development is vital as companies aim to bridge the gap between frontend and backend development. Recent trends show deeper integration between the two, opening numerous possibilities for building real-world web applications, through server-side technologies like Node.js, Express, and MongoDB.
Written by the author of Learning Redux and Learn React Hooks, and CEO of TouchLay, Modern Full-Stack React Projects will guide you through the entire process of advancing from a frontend developer to a full-stack developer. Starting with how to set up robust projects that can be maintained for a long time, you'll then progress toward developing a backend system and integrating it with the frontend. Throughout the book, you'll learn how to build, test, and deploy a blog application and a chat application. You'll also explore MongoDB, Express, React, Node.js (MERN) stack, best practices for frontend and backend development, different full-stack architectures, unit and end-to-end testing, and deployment of full-stack web applications. Once you get to grips with the essential concepts, you'll progress to learn how to use Next.js, an enterprise-grade full-stack web framework for React.
By the end, you'll be well-versed in the MERN stack and all set to create performant and scalable full-stack web applications.
What you will learn
Implement a backend using Express and MongoDB, and unit-test it with Jest
Deploy full-stack web apps using Docker, set up CI/CD and end-to-end tests using Playwright
Add authentication using JSON Web Tokens (JWT)
Create a GraphQL backend and integrate it with a frontend using Apollo Client
Build a chat app based on event-driven architecture using Socket.IO
Facilitate Search Engine Optimization (SEO) and implement server-side rendering
Use Next.js, an enterprise-ready full-stack framework, with React Server Components and Server Actions
Who this book is for
This book is for frontend developers, JavaScript engineers, and React developers who possess a solid understanding of JavaScript and React concepts. Specifically designed for those with limited experience in the development, creation, integration, and deployment of backend and full-stack systems, this book will equip you with the necessary skills to create high-quality web applications.
Table of Contents
Preparing For Full-Stack Development
Getting to Know Node.js, NPM, and MongoDB
Implementing a Backend Service Using Express, Mongoose ODM, and Jest
Integrating Frontend with the Backend Using React and TanStack Query
Deploying the Application with Docker and CI/CD
Adding Authentication and Roles with JSON Web Tokens
Improving the Load Time Using Server-Side Rendering
Making Sure Customers Find You with Search Engine Optimization
Implementing End-to-End Tests Using Playwright
Aggregating and Visualizing Statistics Using MongoDB and Victory
Building a Backend with a GraphQL API
Interfacing with GraphQL on the Frontend Using Apollo Client

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Modern Graph Theory Algorithms with Python: Harness the power of graph algorithms and real-world network applications using Python
English | June 7, 2024 | ASIN: B0CTHRGFF8 | 487 pages | EPUB (True) | 19.73 MB
Solve challenging and computationally intensive analytics problems by leveraging network science and graph algorithms

Key Features
Learn how to wrangle different types of datasets and analytics problems into networks
Leverage graph theoretic algorithms to analyze data efficiently
Apply the skills you gain to solve a variety of problems through case studies in Python
Purchase of the print or Kindle book includes a free PDF eBook
Book Description
We are living in the age of big data, and scalable solutions are a necessity. Network science leverages the power of graph theory and flexible data structures to analyze big data at scale.
This book guides you through the basics of network science, showing you how to wrangle different types of data (such as spatial and time series data) into network structures. You'll be introduced to core tools from network science to analyze real-world case studies in Python. As you progress, you'll find out how to predict fake news spread, track pricing patterns in local markets, forecast stock market crashes, and stop an epidemic spread. Later, you'll learn about advanced techniques in network science, such as creating and querying graph databases, classifying datasets with graph neural networks (GNNs), and mining educational pathways for insights into student success. Case studies in the book will provide you with end-to-end examples of implementing what you learn in each chapter.
By the end of this book, you'll be well-equipped to wrangle your own datasets into network science problems and scale solutions with Python.
What you will learn
Transform different data types, such as spatial data, into network formats
Explore common network science tools in Python
Discover how geometry impacts spreading processes on networks
Implement machine learning algorithms on network data features
Build and query graph databases
Explore new frontiers in network science such as quantum algorithms
Who this book is for
If you're a researcher or industry professional analyzing data and are curious about network science approaches to data, this book is for you. To get the most out of the book, basic knowledge of Python, including pandas and NumPy, as well as some experience working with datasets is required. This book is also ideal for anyone interested in network science and learning how graph algorithms are used to solve science and engineering problems. R programmers may also find this book helpful as many algorithms also have R implementations.
Table of Contents
What is a Network?
Wrangling Data into Networks with NetworkX and igraph
Demographic Data
Transportation Data
Ecological Data
Stock Market Data
Goods Prices/Sales Data
Dynamic Social Networks
Machine Learning for Networks
Pathway Mining
Mapping Language Families - an Ontological Approach
Graph Databases
Putting It All Together
New Frontiers

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Modin for Scalable Data Science: The Complete Guide for Developers and Engineers
English | 2025 | ISBN: None | 509 pages | EPUB (True) | 2.06 MB
"Modin for Scalable Data Science"

In the era of massive datasets and ever-expanding analytics pipelines, "Modin for Scalable Data Science" is a comprehensive guide for data engineers and scientists determined to break through the limits of single-node data workflows. The book opens by analyzing the bottlenecks inherent in contemporary data science, from memory and CPU constraints in pandas to the challenges of distributed data movement. It offers a thorough survey of modern distributed frameworks such as Spark and Dask, before introducing Modin-a breakthrough library that bridges the ease of pandas with the power of distributed computing. Real-world use cases, including large-scale ETL, feature engineering, and interactive analytics, highlight the practical motivations behind adopting scalable data science solutions.
Diving deep into Modin's architecture, the book explores its pluggable execution backends, innovative task graph design, and robust integration with crucial data science and machine learning ecosystems like NumPy, scikit-learn, and RAPIDS. Readers learn best practices for deploying and tuning Modin in diverse environments: from laptops to cloud clusters, containerized solutions via Kubernetes, and advanced resource management in production-grade settings. Thorough attention is paid to security, data locality, and the nuances of environment-specific configuration, ensuring readers gain both strategic understanding and actionable know-how for leveraging Modin at scale.
As a hands-on reference, the book meticulously details Modin's compatibility with pandas, approaches to debugging distributed DataFrames, and advanced profiling and optimization techniques. It empowers practitioners to automate machine learning pipelines, handle real-time inference, and scale MLOps with tools such as Ray Tune and Kubeflow. For those looking to extend or contribute to Modin, the closing chapters provide blueprints for plugin development, internal API mastery, and effective engagement with the open source community. This guide is essential for anyone seeking to harness the full potential of distributed data science without sacrificing the simplicity of familiar Python workflows.

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Modular Relations and Parity in Number Theory
English | 2025 | ISBN: 9819664705 | 275 Pages | PDF EPUB (True) | 17 MB
This book describes research problems by unifying and generalizing some remote-looking objects through the functional equation and the parity relation of relevant zeta functions, known as the modular relation or RHB correspondence. It provides examples of zeta functions introduced as absolutely convergent Dirichlet series, not necessarily with the Euler product. The book generalizes this to broader cases, explaining the special functions involved. The extension of the Chowla-Selberg integral formula and the Hardy transform are key, substituting the Bochner modular relation in the zeta function of Maass forms. The book also develops principles to deduce summation formulas as modular relations and addresses Chowla's problem and determinant expressions for class numbers.

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Money In Crisis: The Return of Instability and the Myth of Digital Cash
English | 2025 | ISBN: 1009390147 | 380 Pages | PDF | 1.3 MB
From its origins in ancient Mesopotamia, through the advent of coinage in ancient Greece and Rome and the invention of paper currency in medieval China, the progress of finance and money has been driven by technological developments. The great technological change of our age in relation to money centres on the creation of digital money and digital payment systems. Money in Crisis explains what the digital revolution in money is, why it matters and how its potential benefits can be realized or undermined. It explores the history, theory and evolving technologies underlying money and warns us that money is in crisis: under threat from inflation, financial instability, and digital wizardry. It discusses how modern forms of digital money (crypto, central bank digital currencies) fit into monetary history and explains the benefits and risks of recent innovations from an economic, political, social and cultural viewpoint.

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Monte Carlo Simluations for Options: Unlocking Precision in Financial Forecasting With Python (Options Pricing with Python Book 2)
English | 2024 | ASIN: B0D8WMMGY8 | 508 pages | PDF | 3.54 MB
Unlock the power of advanced financial modeling with "Monte Carlo Simulations for Options" - the ultimate guide for enthusiasts ready to elevate their understanding of financial derivatives. This book is the ideal follow-up for those who already have a foundation in option pricing and are eager to dive into more sophisticated and nuanced techniques.

Navigate through the intricate world of Monte Carlo simulations applied to financial markets with this comprehensive and accessible resource. Discover how to harness the computational might of Python to create robust models, simulate various market scenarios, and accurately price complex options.
Inside, you will find:
* A detailed introduction to Monte Carlo methods, tailored for financial applications.
* Step-by-step Python tutorials designed to enhance your coding skills and model-building capabilities.
* Advanced strategies for pricing exotic options, handling path dependencies, and managing risk.
* Practical case studies providing real-world insights and actionable strategies.
* Expert tips and best practices to refine your analytic prowess and computational efficiency.
Whether you're a seasoned professional or an avid learner, "Monte Carlo Simulations for Options" offers the knowledge and tools to push the boundaries of your financial acumen. Elevate your expertise and gain a competitive edge in the dynamic world of finance - one simulation at a time.
Prepare yourself for a journey into the depths of financial engineering. With this book as your guide, mastering the art of option pricing has never been more attainable.

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MONTE CARLO SIMULATION: EXCEL APPLICATIONS IN ACCOUNTING AND FINANCE - Beginner Edition
English | 2023 | ASIN: B0CM2FV3HV | 85 pages | Epub | 3.08 MB
This comprehensive guide presents a hands-on, practical approach to understanding and implementing Monte Carlo simulations using Excel. Recognising the ubiquitous nature of Excel in the professional world, this book demystifies complex statistical concepts by transforming them into accessible step-by-step exercises. Readers are provided with an accompanying Excel model, wherein they can actively test various probability distributions, enhancing both their theoretical knowledge and practical skill set. As a result of experienced examples and real-world applications woven throughout the chapters, users are equipped to apply these techniques directly to their own fields of interest or study. From the foundational to the advanced, each concept is broken down with meticulous care, ensuring that readers, irrespective of their prior statistical proficiency, garner a deep, practical understanding. Whether you're a student, a professional, or someone with a burgeoning curiosity about simulations, this guide offers a unique, experiential journey into the world of Monte Carlo simulations in Excel.

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