Altri libri che potrebbero interessarti

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  Data Mining for Beginners - From...

  Simon Winston

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  In our data-driven world, information is the currency of the future, and the ability to mine and extract valuable insights from vast data sets has become an indispensable skill. "Data Mining for Beginners" is your key to unlocking the potential hidden within the world of data. This comprehensive guide is tailor-made for newcomers to data mining, providing a clear and engaging introduction to a field that holds the keys to understanding the patterns, trends, and knowledge that lie within the data all around us. 
  Starting from the ground up, this book takes you on an enlightening journey through the fundamental concepts of data mining, from understanding what data mining is and where data comes from to preprocessing techniques, exploratory data analysis, and a wide array of data mining techniques. You'll learn about machine learning, the algorithms that drive it, and how to evaluate and validate the models you create. 
  The book doesn't stop at theory. It delves into real-world applications across industries such as healthcare, e-commerce, finance, marketing, and more, illustrating how data mining is revolutionizing decision-making, fraud detection, and customer insights. 
  "Data Mining for Beginners" also addresses the ethical considerations and privacy issues that come with the power to mine data, offering guidance on responsible data use. It explores the future of data mining, discussing emerging trends, challenges, and opportunities in the ever-evolving landscape. 
  To help you get started, the book introduces popular data mining tools and provides hands-on examples. It doesn't just aim to educate but also to empower you to take your first steps into the world of data mining. 
   Dive into this fascinating field, unlock the potential of data mining, and embark on a journey to becoming a data mining enthusiast today. 
   

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  Summary of Brittany Hennessy's...

  Falcon Press

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  Buy now to get the main key ideas from Brittany Hennessy's Influencer 
    
  In Influencer (2018), Brittany Hennessy shares a step-by-step approach to becoming a bona fide influencer – from building a community to packaging a brand and monetizing influence, she covers the necessary tools to succeed in the world of influencer marketing. Hennessy also gives readers an inside look at the intricacies of the branded content industry. She shares many expert tips from well-known influencers and includes lengthy Q&A sections with the likes of Sazan Hendrix, Alexandra Pereira, and Joy Cho.

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  Mastering Design Patterns for...

  Manish Saini

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  Master Layered Test Automation and Build Integrate and Deploy with Confidence
  Book Description
  In today’s fast-paced software development landscape, ensuring application quality requires a strategic approach to test automation. Mastering Design Patterns for Layered Testing empowers you with the knowledge and tools to design, implement, and optimize automation across UI, API, and backend layers using Python’s powerful ecosystem.
  Starting with foundational concepts like test design patterns and the Test Pyramid, the book delves into practical implementations of unit testing, integration testing, API testing, and contract testing. You’ll learn how to integrate automated tests into CI/CD pipelines using GitHub Actions, generate detailed test reports with Allure, and address modern testing challenges such as microservices and containerized environments. Real-world case studies illustrate how to apply these techniques in production settings.
  A dedicated chapter on Generative AI in testing explores its applications in test case generation and test data creation. Whether you're an intermediate tester looking to enhance your automation skills or an experienced professional seeking to learn advanced strategies, this book provides the expertise needed to build scalable and reliable test automation frameworks that drive software quality and efficiency. Stay ahead of the curve—master next-gen test automation before it’s too late!
  Table of Contents
  1. Introduction to Strategic Test Design
  2. Understanding Test Design Patterns
  3. Unit Testing Strategies
  4. Integration Testing Approaches
  5. API Testing Techniques
  6. Contract Testing
  7. Distributing Tests Across UI, API, and Backend Layers
  8. Integrating Tests into CI/CD Pipelines
  9. Advanced CI/CD Strategies
  10. Future of Test Automation
  11. Leveraging Generative AI in Testing      
  
  Index

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  Python Data Analysis for...

  Brian Murray

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  Python Data Analysis for Beginners: A Beginner's Handbook to Exploring and Visualizing Data is a comprehensive guide designed to help readers master the fundamentals of data analysis using the Python programming language. Whether you're a beginner looking to get started with data analysis, or a professional looking to expand your skill set, this book provides a step-by-step approach to exploring and visualizing data with Python. 
  The book starts with an introduction to Python programming language and its essential libraries for data analysis. Readers will learn how to manipulate and transform data using Pandas library, and how to create visualizations using Matplotlib and Seaborn libraries. The book also covers exploratory data analysis (EDA) techniques using Python, including data preprocessing and visualization techniques. 
  In addition, the book introduces readers to machine learning concepts and provides an overview of supervised and unsupervised learning using Python. The book includes several case studies and real-world applications of data analysis using Python, including analyzing and visualizing social media data, financial data, and healthcare data. 
  Written in a clear and concise language, Python Data Analysis for Beginners provides readers with a solid foundation in data analysis using Python. The book is suitable for self-learners, as well as instructors teaching data analysis to students. With its step-by-step approach and real-world examples, this book is an essential resource for anyone looking to master data analysis with Python. 
   

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  Over the Seawall - Tsunamis...

  Stephen Robert Miller

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  In March 2011, people in a coastal Japanese city stood atop a seawall watching the approach of the tsunami that would kill them. They believed—naively—that the huge concrete barrier would save them. Instead they perished, betrayed by the very thing built to protect them. Erratic weather, blistering drought, rising seas, and ecosystem collapse now affect every inch of the globe. Increasingly, we no longer look to stop climate change, choosing instead to adapt to it. 
   
   
   
  Never have so many undertaken such a widespread, hurried attempt to remake the world. Predictably, our hubris has led to unintended—and sometimes disastrous—consequences. Academics call it maladaptation; in simple terms, it's about solutions that backfire. Over the Seawall tells us the stories behind these unintended consequences and the fixes that can do more harm than good. From seawalls in coastal Japan, to the reengineered waters in the Ganges River Delta, to the artificial ribbon of water supporting both farms and urban centers in parched Arizona, Stephen Robert Miller traces the histories of engineering marvels that were once deemed too smart and too big to fail. In each he takes us into the land and culture, seeking out locals and experts to better understand how complicated, grandiose schemes led instead to failure, and to find answers to the technologic holes we've dug ourselves into.

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  The Cycling City - Bicycles and...

  Evan Friss

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  Cycling has experienced a renaissance in the United States, as cities around the country promote the bicycle as an alternative means of transportation. In the process, debates about the nature of bicycles—where they belong, how they should be ridden, how cities should or should not accommodate them—have played out in the media, on city streets, and in city halls. Very few people recognize, however, that these questions are more than a century old. 
   
  The Cycling City is a sharp history of the bicycle’s rise and fall in the late nineteenth century. In the 1890s, American cities were home to more cyclists, more cycling infrastructure, more bicycle friendly legislation, and a richer cycling culture than anywhere else in the world. Evan Friss unearths the hidden history of the cycling city, demonstrating that diverse groups of cyclists managed to remap cities with new roads, paths, and laws, challenge social conventions, and even dream up a new urban ideal inspired by the bicycle. When cities were chaotic and filthy, bicycle advocates imagined an improved landscape in which pollution was negligible, transportation was silent and rapid, leisure spaces were democratic, and the divisions between city and country were blurred. Friss argues that when the utopian vision of a cycling city faded by the turn of the century, its death paved the way for today’s car-centric cities—and ended the prospect of a true American cycling city ever being built.

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