Weitere Bücher, die Sie mögen werden

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  No-Code App Development for...

  Johnny Nelson

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  You don’t need to be a programmer to build powerful apps, launch stunning websites, or automate online businesses. No-Code App Development for Beginners: Build Websites, Automations, and Online Businesses Without Writing Code is the ultimate beginner’s guide to creating digital products and launching ventures—without touching a single line of code. 
  Perfect for entrepreneurs, freelancers, side-hustlers, and curious creators, this audiobook unlocks the world of no-code tools like Webflow, Bubble, Glide, Zapier, Airtable, and more. You’ll discover exactly how everyday people are turning simple ideas into high-impact apps, landing pages, eCommerce stores, and income-generating digital products—fast, affordably, and without traditional tech skills. 
  With step-by-step guidance and real-world case studies, this comprehensive blueprint shows you how to validate your idea, choose the right no-code platforms, design user-friendly interfaces, and automate business workflows. Whether you want to build a client portal, subscription platform, inventory tracker, or MVP for a startup, this audiobook gives you the confidence to bring your vision to life. 
  Gone are the days when coding was a barrier to innovation. No-code is reshaping the digital economy, leveling the playing field, and empowering a new wave of makers to launch apps and startups on their own terms. If you’ve got a business idea or a dream project, now’s the time to build it. 
  No-Code App Development for Beginners will help you take that first step—and build something amazing. 
  You have the tools. You have the vision. You don’t need the code. Just press play.

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  The Impact of Technology on...

  Craig Dames

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  Technology has long been a driving force in shaping the nature of employment. From the Industrial Revolution to the digital age, advancements in technology have continuously altered the way people work, the skills required, and the overall structure of industries. In today's fast-evolving world, the relationship between technology and employment is more complex than ever. While technological progress brings efficiency, innovation, and new job opportunities, it also presents significant challenges such as job displacement, skill gaps, and the need for constant adaptation. Understanding this dynamic is crucial for individuals, businesses, and policymakers as they navigate the ever-changing landscape of work. 
  The evolution of technology in the workforce has been marked by transformative shifts that redefine how labor is performed. Historically, the introduction of machines, automation, and digital tools has led to the replacement of certain manual and repetitive tasks. However, rather than eliminating jobs entirely, these changes have often resulted in the creation of new roles that require different skill sets. For example, while the rise of automated assembly lines reduced the need for traditional factory workers, it also increased demand for engineers, technicians, and software developers to maintain and improve these systems. Similarly, the widespread adoption of computers and the internet revolutionized industries by enabling remote work, e-commerce, and data-driven decision-making, further expanding employment opportunities in the digital sector.

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  Machine Learning Made Simple -...

  Emily Johnson

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  The book "Machine Learning Made Simple: Essential Techniques for Modern Data Analysis" is a complete guide meant to make the basic ideas and methods of machine learning easy to understand. This book breaks down complicated ideas and gives useful information for people who are just starting to learn about data analysis. 
  The readers will learn about different kinds of machine learning, like controlled, unsupervised, and reinforcement learning, and how they can be used to fix problems in the real world. The book talks about important algorithms, methods for preparing data, and evaluation measures that help readers get a good grasp of how machine learning works. 
  There are tasks, case studies, and real-life examples in every chapter to help readers put what they've learned to use and solidify what they've learned. This book gives readers the tools they need to use machine learning solutions in many areas, including business, healthcare, finance, and technology, by focusing on real-world examples. 
  This book is helpful for anyone who wants to use the power of data, since machine learning is still changing businesses and leading to new ideas. "Machine Learning Made Simple" gives you the tools and information you need to start your machine learning journey with confidence and clarity, no matter if you are a student, a worker, or just a curious fan.

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  Streaming Data Mesh - A Model...

  Hubert Dulay, Stephen Mooney

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  Data lakes and warehouses have become increasingly fragile, costly, and difficult to maintain as data gets bigger and moves faster. Data meshes can help your organization decentralize data, giving ownership back to the engineers who produced it. This book provides a concise yet comprehensive overview of data mesh patterns for streaming and real-time data services. 
   
   
   
  Authors Hubert Dulay and Stephen Mooney examine the vast differences between streaming and batch data meshes. Data engineers, architects, data product owners, and those in DevOps and MLOps roles will learn steps for implementing a streaming data mesh, from defining a data domain to building a good data product. Through the course of the book, you'll create a complete self-service data platform and devise a data governance system that enables your mesh to work seamlessly. 
   
   
   
  With this book, you will design a streaming data mesh using Kafka; learn how to identify a domain; build your first data product using self-service tools; apply data governance to the data products you create; learn the differences between synchronous and asynchronous data services; and implement self-services that support decentralized data.

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  Deep Learning Bitcoin Price...

  Bryan DeHart

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  This podcast explores the use of deep learning to predict Bitcoin price direction. Several deep learning models, including CNN-LSTM, LSTNet, and TCN, are compared to an ARIMA model as a benchmark. Feature selection methods are employed to optimize model performance. The results show that the combination of Boruta feature selection with the CNN-LSTM model outperforms others, achieving an accuracy of 82.44% and generating extraordinary annual returns in simulated investment strategies. The study highlights the potential of predictive models in Bitcoin trading, while acknowledging limitations and suggesting areas for future research.

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  How To: GPT-4 for Financial...

  Ben Jakobsen

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  Discover the ultimate guide to starting a lucrative online business or side hustle using the groundbreaking power of GPT-4 and its innovative plugins. If you've ever dreamed of making money online, this book is for you! 
  How To: GPT-4 for Financial Freedom is tailored specifically for aspiring entrepreneurs and side hustlers eager to carve out their own path to success in the digital world. This comprehensive guide dives deep into the potential of GPT-4 and its game-changing plugins, unlocking the secrets to easily building a thriving online venture. 
  In this book, you'll learn how GPT-4 and its plugins can revolutionize how you approach online businesses, dramatically reducing the effort needed to succeed. With this knowledge, you'll be equipped to disrupt a wide array of existing industries and create your own profitable niche. 
  Get ready to:Start your online business or side hustle with confidence and easeHarness the power of GPT-4 plugins to streamline your operations and boost profitabilityDisrupt existing business models and reshape the digital landscape 
  Don't miss this opportunity to transform your online aspirations into reality. Start your journey to financial freedom and entrepreneurial success with How To: GPT-4 for Financial Freedom today!

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