Books

Josh saw the shooting outside his college. His AI headset did not let him see the people who carried it out. Three milliseconds earlier, a routine safety update had changed the rules.

The latest version of Rust (1.85) has some great new features, like async closures, more stable associated function return types, and const generics that are now mature enough to underpin serious numerical libraries. The linfa and smartcore ecosystems have developed into decent classical machine learning stacks. The Burn training framework feels native to Rust, not like it's been ported from it. The Candle makes it so that loading pre-trained transformer models is more of an engineering task than a research exercise. The crates that used to need all sorts of workarounds now just work.

Turn data into intelligent decisions. Discover how machine learning works and learn to build predictive models using Python and Scikit-Learn. From data preprocessing and visualization to classification, regression, clustering, and model evaluation, this practical guide helps you develop real-world machine learning skills.

AI won’t replace people who know how to adapt—it will empower them. In a world transformed by artificial intelligence, your greatest advantage is not technology, but your ability to think critically, learn continuously, build meaningful relationships, and act with purpose. Discover the human skills that machines cannot replicate and learn how to stay relevant, productive, and future-ready.

Rewiring Software Delivery shows technology leaders how to move beyond AI tool adoption and redesign the operating model for agentic engineering. It introduces practical ways to govern autonomous execution, strengthen intent, separate generation from validation, and build a delivery system that turns AI activity into durable business advantage.

The most important impact of AI on software development isn't that it writes code faster — it's that it changes what you can delegate. Agentic Programming is a practical roadmap for climbing the AI Fluency Ladder: from prompting to agentic workflows, verified execution, and ultimately autonomous software development.

Prepare for senior Go interviews, or for the jump from mid-level to senior, with a focus on AI platform engineering: LLM gateways, RAG, vector search, Kubernetes, observability, concurrency ownership, and production failure modes. Includes interview questions, senior-level answer rubrics, executable Go examples, and a production-oriented RAG service capstone you can run, test, break, and explain.

Find out in minutes what obligations you face under the EU AI Act - before it becomes a problem.

The EU AI Act is messy, confusing, and unavoidable. Get compliant before it becomes a problem.

Practical, safe AI for people who actually run networks.

The No-Jargon Guide for Everyday Workers Who Want to Save Time, Get Ahead, and Stop Feeling Left Behind. **91% of companies say they use AI. Only 21% of workers actually do. Close the gap in 30 days — no computer science degree required.**

You leave Claude Code running and come back to something missing. This book is arranged by the accident, not the mechanism: databases dropped, files deleted, git history rewritten, the rewind command taking work with it. Three of the four get the exact hook that blocks the command before it runs, with the recovery if it already happened; no PreToolUse hook sees the rewind command, and the book gives the settings-level lever and names the one place a refusal could still live. Appendix B prints all 195 commands the guards were fired at, refusals and allowances both.

From LLMs and RAG to Memory, MCP, Agent Frameworks and Enterprise AI Controls—discover how modern AI Agents work internally within today's rapidly evolving AI ecosystem.

Every web application has security headers, cookies, TLS configurations, and CORS policies that need to be correct. Most teams find out they're wrong only after a penetration test — or worse, after an incident. This book shows you how to build a scanner that catches these issues automatically. You'll create a Python CLI tool that uses Hurl (declarative HTTP testing) to assert security properties, SSLyze to validate TLS protocol versions, and AI to generate specific remediation for every failure it finds. The output: structured JSON reports, visual HTML dashboards, and AI-generated security posture assessments. **What you'll build:** - 9 declarative Hurl security test files (headers, cookies, CORS, HSTS, CSP, CSRF, redirects, TLS) - A preprocessor that handles domain substitution and authentication - An output parser with built-in remediation guidance for every test - A TLS scanner validating SSL 2.0/3.0 disabled and TLS 1.2/1.3 enabled - An AI analyzer that generates context-specific fixes using Ollama, OpenAI, or Bedrock - An HTML reporter with dark-themed visual dashboards - Docker multi-architecture deployment - CI/CD pipeline with GitHub Actions **Who this is for:** - Developers who want security checks before deploying - DevSecOps engineers building CI/CD security gates - Penetration testers who need quick baseline assessments - Security students learning web vulnerability concepts hands-on - Platform teams enforcing security standards across services Every failure includes: what was expected, what was received, why it matters, how to fix it, and a documentation link. AI adds domain-specific code examples on top.

Every web application has security headers, cookies, TLS configurations, and CORS policies that need to be correct. Most teams find out they're wrong only after a penetration test — or worse, after an incident. This book shows you how to build a scanner that catches these issues automatically. You'll create a Python CLI tool that uses Hurl (declarative HTTP testing) to assert security properties, SSLyze to validate TLS protocol versions, and AI to generate specific remediation for every failure it finds. The output: structured JSON reports, visual HTML dashboards, and AI-generated security posture assessments. **What you'll build:** - 9 declarative Hurl security test files (headers, cookies, CORS, HSTS, CSP, CSRF, redirects, TLS) - A preprocessor that handles domain substitution and authentication - An output parser with built-in remediation guidance for every test - A TLS scanner validating SSL 2.0/3.0 disabled and TLS 1.2/1.3 enabled - An AI analyzer that generates context-specific fixes using Ollama, OpenAI, or Bedrock - An HTML reporter with dark-themed visual dashboards - Docker multi-architecture deployment - CI/CD pipeline with GitHub Actions **Who this is for:** - Developers who want security checks before deploying - DevSecOps engineers building CI/CD security gates - Penetration testers who need quick baseline assessments - Security students learning web vulnerability concepts hands-on - Platform teams enforcing security standards across services Every failure includes: what was expected, what was received, why it matters, how to fix it, and a documentation link. AI adds domain-specific code examples on top.