Altri libri che potrebbero interessarti

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  The Developer's Playbook for...

  Steve Wilson

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  Large language models (LLMs) are not just shaping the trajectory of AI, they're also unveiling a new era of security challenges. This practical book takes you straight to the heart of these threats. Author Steve Wilson, chief product officer at Exabeam, focuses exclusively on LLMs, eschewing generalized AI security to delve into the unique characteristics and vulnerabilities inherent in these models. 
   
   
   
  Complete with collective wisdom gained from the creation of the OWASP Top 10 for LLMs list—a feat accomplished by more than 400 industry experts—this guide delivers real-world guidance and practical strategies to help developers and security teams grapple with the realities of LLM applications. Whether you're architecting a new application or adding AI features to an existing one, this book is your go-to resource for mastering the security landscape of the next frontier in AI. You'll learn: 
   
   
   
  ● Why LLMs present unique security challenges 
   
   
   
  ● How to navigate the many risk conditions associated with using LLM technology 
   
   
   
  ● How to identify the top risks and vulnerabilities associated with LLMs 
   
   
   
  ● Methods for deploying defenses to protect against attacks on top vulnerabilities 
   
   
   
  ● And more

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  Before I Begin: A Manifesto on...

  Hatem Helmy

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  Before I Begin: A Manifesto on Humanity's Reckoning and the End of the World is not just another book about apocalypse. It is a bold philosophical and scientific exploration of the greatest threats humanity has ever faced—and the hidden patterns that link our past extinctions to the dangers of today. 
  From the cataclysmic asteroid that wiped out the dinosaurs to the looming possibility of nuclear war, from supervolcanoes and gamma-ray bursts to engineered viruses and runaway artificial intelligence, this manifesto examines how fragile our existence truly is. But beyond the science of survival, it confronts the uncomfortable truth: that corruption, inequality, and the failures of the global system may be the gravest threats of all. 
  In powerful, provocative prose, Hatem Helmi weaves together history, philosophy, and cutting-edge science to reveal a vision of humanity standing on the edge of transformation. Will we collapse into chaos, or will we seize the chance to build a more just and resilient world? 
  For readers of Yuval Noah Harari, Stephen Hawking, and Jared Diamond, this book is both a warning and a manifesto—a call to awaken, to question, and to act before it is too late. 
  This is not the end. It is the beginning of a reckoning. 

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  Mobile App Development: Crafting...

  Jordan Mitchell

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  When starting the thrilling path of creating your first mobile application, "Mobile App Development: Crafting Innovative Digital Experiences: A Beginner's Guide to Building Your First Mobile Application" is a must-have companion. Designed with novices in mind, this thorough manual simplifies the intricate process of developing apps into digestible, step-by-step instructions. 
  From exploring various types of mobile applications to navigating the entire development process, this book is a practical guide from start to finish. It will equip you with the skills to generate and refine app concepts, conduct effective market research, and devise a robust project strategy. You'll also delve into the essentials of user interface (UI) and user experience (UX) design, ensuring your app is not just visually appealing, but also user-friendly. 
  Whether setting up your development environment, selecting the most suitable programming languages and tools, or building your app from scratch, this book has you covered. It leaves no stone unturned, even delving into advanced topics like backend integration, security, performance optimization, and thorough testing to ensure your software is robust, secure, and efficient. 
  As the final phases draw near, learn how to properly launch and market your app and get advice on keeping it updated and maintained when it's live. This book gives you the information and abilities to bring your creative ideas to life and create engaging digital experiences, whether you're an aspiring developer or an entrepreneur with a vision.  
   

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  Hands-on NumPy for Numerical...

  Rituraj Dixit

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  Unlock the Power of NumPy to Accelerate Data Analysis and Computing.
  Book Description
  NumPy is the backbone of numerical computing in Python, powering everything from scientific research to machine learning and AI applications. Mastering NumPy is essential for anyone working with data, enabling faster computations, efficient data structures, and seamless integration with advanced analytical tools.
  Hands-on NumPy for Numerical Analysis is a comprehensive guide that takes you from the fundamentals of NumPy to its advanced applications. Through hands-on examples and real-world scenarios, this book equips data scientists, analysts, and machine learning engineers with the practical skills needed to manipulate large datasets and optimize performance. Key topics include array operations, linear algebra, signal processing, and machine learning implementations, all covered with detailed explanations and step-by-step guidance.
  Whether you're building your foundation in numerical computing or looking to enhance your data analysis workflows, this book will give you a competitive edge. Don't get left behind—harness the full power of NumPy to supercharge your data science and machine learning projects today!
  Table of Contents
  1. Getting Started with NumPy
  2. Understanding NumPy Array
  3. Data Type (dtype) in NumPy Array
  4. Indexing and Slicing in NumPy Array
  5. NumPy Array Operations
  6. NumPy Array I/O
  7. Linear Algebra with NumPy
  8. Advanced Numerical Computing
  9. Exploratory Data Analysis
  10. Performance Optimization
  11. Implementing a Machine Learning Algorithm      
  
  Index

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  Game Theory - Applications to...

  Daniel Shore

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  Here are some fundamental concepts and terms in game theory and economics: 
    
  Game Theory: A branch of mathematics and economics that studies how people make decisions in strategic situations, where the outcome of one person's decision depends on the decisions of others. 
    
  Players: Individuals, groups, or entities making decisions in a game. Each player typically has a set of possible actions they can take. 
    
  Strategy: A plan of action for a player that specifies what they will do in each possible situation or contingency in the game. 
    
  Payoff: The outcome or result that a player receives as a consequence of their actions and the actions of others in the game. Payoffs are often represented in terms of utility, profits, or some other measurable outcome. 
    
  Nash Equilibrium: A concept in game theory where no player has an incentive to unilaterally change their strategy, given the strategies chosen by the other players. In other words, each player's strategy is optimal given the strategies chosen by the other players.

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  Deep Learning with Python - A...

  Brian Murray

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  Deep Learning with Python is a comprehensive guide to building and training deep neural networks using Python and popular deep learning frameworks. Whether you are a beginner or an experienced data scientist, this book provides a detailed understanding of the theory and practical implementation of deep learning. 
  Starting with an introduction to deep learning, the book covers essential topics such as neural network architecture, training and optimization, regularization, and transfer learning. It also covers popular deep learning frameworks such as TensorFlow, Keras, and PyTorch. 
  The book includes practical examples and step-by-step instructions to help you build and train deep neural networks for a variety of applications, including image and speech recognition, natural language processing, and time series analysis. You will also learn how to use advanced techniques such as convolutional neural networks, recurrent neural networks, and generative adversarial networks. 
  With its comprehensive coverage of deep learning and practical examples, this book is an essential resource for anyone interested in building and training deep neural networks using Python and popular deep learning frameworks. 
   

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