Preventa de eBooks de Programación y lenguajes

A unique approach to building trustworthy AI systems with open-source tools, combining hands-on projects, real-world relevance, and a focus on innovation and collaboration.Build Your Own AI is your practical, creative guide to building ethical and impactful AI systems using todays most powerful open-source tools.Clear, jargon-free explanations will walk you through libraries like PyTorch, TensorFlow, and Keras as you build classifiers, character predictors, and digit recognizers. Youll also explore advanced topics like MLOps, AI security, and responsible AI development, putting tools such as Hugging Face, LangChain, CrewAI, ANOVA, and SHAP into action.Through hands-on projects like predicting superhero feats, generating story plotlines, and crafting and detecting deepfakes, youll combine technical insight with imaginative exploration. Youll even build a trivia game powered by agentic bots using top-tier models like LLaMA, Whisper, and Stable Diffusion.By the end, youll know how to build and deploy AI systems and be ready to confidently join the global open-source AI movement. Walk through that door today with Build Your Own AI.

Learn to build a web app that can monitor millions of posts across all social media platforms to chart public opinion in real time.Social media has become our modern-day agora, the place where we get our news and engage in political discourse. With disinformation, hate speech, foreign interference, authoritarianism, market monopolization, and political polarization all on the rise, monitoring social media in the public interest has never been so difficult nor so urgent. Social Media Exposed is an in-depth beginners guide to coding full-stack web applications in Python to track and analyze social media activity at scale, giving you unparalleled insights into the cultural and political conversations of our time, then empowering you to reach your own conclusions.Youll start by coding a web app to monitor Russian disinformation channels discussing Ukraine on Telegram, then learn more adversarial methods to scrape the Wayback Machine, Instagram, and TikTok. Youll detect Twitter bots following Saudi influencers, extract text-embedded URLs to reveal a white supremacist blogosphere, parse archived tweets to reveal the discourse leading up to the January 6 insurrection, and learn to circumvent Metas and ByteDances defenses to scrape Instagram and TikTok, collecting evidence of war crimes in the Middle East. Finally, youll write an API and deploy your observatory to a cloud server to collaborate with other investigators. By the end of the book, youll have a working website that allows collaborators to log in, request data collection, and perform analysis of collected data, via a point-and-click interface. Along the way, youll learn to: Use Python and RabbitMQ to retrieve Telegram data from a remote API Store data with PostgreSQL and query it with SQLAlchemy Analyze the data youve retrieved with Pandas, NetworkX, Gephi, and other tools Use state-of-the-art AI tools to transcribe audio and classify text Deploy a website with an interactive dashboard using FastAPI, Dash, Cytoscape, Uvicorn, Gunicorn, Nginx, AWS, and Lets Encrypt Containerize your apps with Docker and provision infrastructure with Pulumi Whether youre a citizen scientist, a security researcher, a journalist, an activist, or a scholar, Social Media Exposed is an essential blueprint for building your window into online worlds.

Readers of all backgrounds will learn about cryptographys role in protecting everyday digital interactions from buying a coffee to texting a friend from two security experts.This cybersecurity book for beginners and experts alike offers an engaging exploration of cryptographys role in our everyday lives.Matthew Green, professor at Johns Hopkins and creator of the Zcash cryptocurrency, and Yehuda Lindell, Head of Cryptography at Coinbase, demystify the technologies that keep our information safe behind the scenes during common digital interactions, including: Tapping to pay for your morning coffee Texting friends or emailing coworkers Shopping on your favorite website Sharing your location with GPS appsBy distilling complex topics like encryption and digital signatures into clear, approachable explanations, Cryptography for Everyone equips readers to navigate the digital world more safely. Along the way, the authors discuss the potential downsides of cryptography, noting its use in hiding criminal activities and the ongoing debate around government surveillance.To do its job, cryptography should be tough to crack, but that doesnt mean it has to be mysterious. Learn how youre kept safe online and make more informed decisions about your privacy and security with Cryptography for Everyone.

A practical, accessible guide that shows working software developers how to integrate real AI features into the applications they already buildusing JavaScript, Python, APIs, and modern cloud services, without needing a data-science background.Most developers already know AI is powerful. What they dont know is how to actually use it in their own codebase without becoming a data scientist. Too often, AI features stall out at brittle prototypes, half-baked search functions, or smart features that collapse the moment requirements change. Thats where this book comes in. We wrote this book with the everyday software developer in mind. The dev who works in a company and wants to grow their career by meeting the demands of the industry without losing time in the areas that might not be relevant to their current company or role.Written by seasoned developers Jacob Orshalick, Jerry M. Reghunadh, and Danny Thompson, this book teaches you how to integrate and customize large language models (LLMs) and other pre-trained AI models to solve real-world problems. Instead of drowning you in theory, this book gives you: Intelligent automation: Automate repetitive work by calling LLMs directly from your own applications and streaming intelligent responses to the UI. Practical Paths: Build production-ready AI features with tools you already know and some you dont. Clarity through the hype: Learn where AI actually makes sense in your applications (and where it doesnt). Fewer dead-ends: Avoid wasted cycles by understanding limitations, costs, and trade-offs before you build. Competitive edge: Discover how AI can help you improve search, personalization, automation, and more.

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Vous pensiez que les programmeurs étaient des espèces de magiciens venus dun pays imaginaire et dotés de pouvoir magiques ? Croyez-le ou non, mais ce livre va vous montrer quun humain ordinaire peut

AI can write the code. You still need to know what it does.Youre already good at Excel. But youre tired of the copy/paste, the helper columns, and the brittle formulas that break when someone adds a row. You want automation, and whether you write the code yourself or let AI generate it, you need to understand whats actually running your business processes.Automate Excel with Python teaches you to build real workflows, step-by-step. Youll read messy workbooks into pandas dataframes, filter and reshape data without helper columns, merge sources without silent VLOOKUP failures, and export polished results with formatting intact. A capstone chapter ties it together: import a multi-tab workbook, generate exception reports, and email the resultsall from one script you run with a single click.Youll learn how to: Read existing Excel files you already use into Python, even the messy ones Replace daily copy/paste routines with reusable scripts Merge and match data across sources with auditable results Handle dates, times, and the edge cases that break formulas Export from Python to Excel with column widths, number formats, and frozen panes intact Build workflows that run daily without babysitting AI can write the code. This book makes sure youre the one in control of it.

A no-nonsense guide to all the essentials youll need to become a TypeScript wizard and build a TypeScript application from scratch.An invaluable resource to countless developers.Ryan Cavanaugh, Development Lead Microsoft TypeScript Team TypeScript makes JavaScript safer and your editor smarter. Matt Pococks Total TypeScript courses have trained thousands of developers by putting the editor first: You learn types by watching what TypeScript tells you, not by memorizing rules. This book brings that method to print.Youll start by setting up a proper TypeScript environment, then immediately begin writing and annotating code. Each chapter builds on the lastprimitive types to unions, objects to classes, basic generics to type transformationswith exercises woven throughout as checkpoints, not afterthoughts.Later chapters tackle what takes longer to learn: deriving types from other types, writing type predicates and assertion functions, configuring the compiler for real projects, and building type architectures that dont collapse under their own weight.Youll learn to: Read TypeScripts error messages and use your editor as a teaching tool Write precise types for objects, functions, and classes Use unions, narrowing, and generics to make types flexible without losing safety Derive and transform types so you dont repeat yourself Configure tsconfig.json for React, Node, or library development This is a workshop in print. The one Matt Pocock has been refining for years.

Build stable, production-grade systems with Rust.The Rust Programming Language, 3rd Edition, teaches you to write code that the compiler can verify, teams can maintain, and systems can evolve safely over time. Written by longtime Rust community members, this book shows you how to work effectively with Rusts type system, concurrency model, and tooling, using patterns and idioms chosen for long-term stability.Learn how to: Design programs that communicate their invariants to the compiler Use ownership, lifetimes, and traits to model real-world constraints Write concurrent and multithreaded code with confidence and clarity Build, test, document, and refactor projects using Cargo effectively Handle errors explicitly and idiomatically Apply expressive pattern matching to simplify complex logic Three substantial project chaptersfocusing on a number-guessing game, a command-line tool, and a multithreaded serverdemonstrate how these concepts work together in complete, real programs.Whether youre new to Rust or already using it in production, this book helps you write code that scales safely and makes its guarantees explicit.New to this edition: Complete async programming chapter Miri for analyzing unsafe code Built on the Rust 2024 Edition Modern Rust idioms, tooling, and practices

A project-driven guide to designing, training, and deploying artificial intelligence directly on embedded hardware, showing how to build intelligent, autonomous systems under real-world constraints.Embedded AI is a hands-on, hardware-first guide to building intelligent systems that run locally, in real time, on microcontrollers and single-board computers. Rather than focusing on theory or isolated case studies, the book emphasizes practical design decisions and the trade-offs engineers face when deploying AI on constrained devices.Readers begin with the foundations of embedded systems and machine learning, then learn how to collect, explore, and preprocess sensor data. The book places particular emphasis on exploratory data analysis, feature engineering, and data qualityareas that are critical to embedded machine learning but often overlooked.Using popular platforms such as Arduino, Raspberry Pi, STM32, and Seeed Studio boards, readers work through concrete projects including battery monitoring, hot-word detection, gesture recognition, noise classification, occupancy detection, and intelligent control systems. Industry-standard tools such as scikit-learn, TensorFlow Lite, and Edge Impulse are introduced only to the extent needed to support real projects.Advanced chapters address sensor fusion, power management, model compression, security, and privacy, helping readers understand how to build systems that are not just intelligent, but robust and deployable. The book concludes with a biologically inspired approach to embedded intelligence using the open-source Primal Layers framework, culminating in an embedded AI robot project.

A practical, experiment-driven introduction to deep learning that shows programmers how modern neural networks actually work by running, inspecting, and reasoning about real models, from foundational concepts through large language models.How Deep Learning Works is for programmers who want to understand deep learning, not just use it.Rather than starting with heavy math or abstract theory, this book takes an experiment-first approach. Each chapter walks readers through carefully designed experiments using real deep learning toolkits, guiding them step by step from running code to understanding why models behave the way they do. A consistent structureoverview, execution, code review, and discussionkeeps readers oriented and focused on building intuition, not memorizing APIs.Beginning with fundamental ideas like classification and neural networks, the book steadily builds toward modern techniques, including transfer learning, zero-shot and few-shot models, and hands-on experiments with large language models. Along the way, readers learn how to spot failure modes, reason about trade-offs, and adapt existing tools to new problems.The result is a clear, software-centric explanation of deep learning that helps working programmers move beyond copy-paste ML and develop real understanding they can apply in their own projects.