Books

Lisp languages are a secret weapon! Use the modern Gerbil Scheme for AI and other applications.

Este livro aborda a Simulação de Eventos Discretos por uma perspectiva que, metodologicamente, satisfaça a cada etapa que um projeto de simulação exija para ser bem-suce­dido. São aprofundados os conceitos fundamentais, mas sem perder a prática de como fazer.

A how-to field guide on building leak-free abstractions and algebraically designing real-world applications.

You are given the main technologies implemented and the connectivity required and you are required to fix it ;)

Descriptions, Discussion, and Selected Source Modules illustrating State Machines, Event Handlers, Message Pumps, Fibers, and Event-triggered, Interacting State Machines. A demo program can be downloaded and run on an STM32F746G_DISCO board.

Describes the most commonly used patterns and principles for creating modern Apache Camel applications. Each pattern is based on a real world use case and provides Camel specific implementation details and best practises.

You don't need to code AI to understand its impact.Thinking Beyond Code: A Human’s Guide to Artificial Intelligence takes readers beyond algorithms and programming to explore the questions that matter most in an AI-powered world.How do machines learn? Can AI really think? Can machines be creative? What happens to jobs when automation expands? Who is responsible when an AI system makes a decision? Can AI-generated content change our understanding of truth? And what might happen if increasingly capable AI systems become part of everyday human life?From machine learning and neural networks to creativity, ethics, employment, deepfakes, AGI, and human-AI collaboration, this book offers an accessible journey through the technology and the human questions surrounding it.Understand the technology. Question the assumptions. Think beyond the code.

A practical guide to modern computer architecture, high-performance systems, microarchitecture, parallelism, and evidence-based performance analysis.

Documents that drive action: test plans people read, bug reports that get fixed, RCAs that prevent repeats, and docs that outlive team turnover.

Move beyond prompt experimentation. Build governed Claude AI workflows for FP&A, forecasting, close, reporting, document review, reconciliation, and finance controls—then practise with 20 hands-on exercises and worked solutions in the included GitHub Companion Pack.

Every organization struggles with waste—lost time, hidden costs, and inefficient processes that drain performance. This book introduces you to the mindset and principles of Value Stream Mapping (VSM), showing how to see waste clearly, understand its impact, and build the foundation for continuous improvement.

Test your C++ knowledge. Strengthen your programming concepts. Improve your coding skills. Prepare confidently for university examinations, placements, and software interviews.Mastering C++ Programming QUESTION BANK: 1000+ Conceptual Questions for Students and Professionals

Benefits of Studying This Book 1. Deep Conceptual Understanding You will understand why AI algorithms work, not just how to run them. This allows you to innovate, debug, and improve models. 2. Career Advantage Strong mathematical foundations make you stand out in interviews for AI, ML, and DS roles. Many recruiters test candidates on linear algebra and probability skills. 3. Research Readiness Postgraduate students and researchers can directly apply these mathematical tools to design and analyze experiments. 4. Practical AI Skills Python-based implementation examples ensure that you can directly apply mathematical concepts in real-world AI systems. 5. Interdisciplinary Edge Mathematics learned here is not limited to AI — it can be applied in robotics, quantum computing, finance, bioinformatics, and more. How This Book Helps After StudyAfter completing this book, you will be able to:·        Build AI models from scratch, knowing exactly what mathematical operations are happening inside.·        Optimize models for performance using a deep understanding of linear algebra operations.·        Analyze and interpret model predictions probabilistically.·        Handle uncertainty and noise in datasets effectively.·        Implement advanced AI concepts like PCA, SVD, Bayesian inference, and Markov models without relying solely on pre-built libraries.This knowledge will directly help in:·        Academics: Scoring well in AI/ML/DS university courses.·        Industry: Working as an AI engineer, data scientist, ML engineer, or research scientist.·        Competitive Exams: Preparing for GATE, NET, and other AI-related exams where mathematics is heavily tested.·        Research: Publishing papers where mathematical rigor is required to explain new AI techniques. 

A Sample Learning Journey with This Book Imagine a final-year MCA student who needs to select a project topic.·        After Chapter-3, they can identify a novel, research-worthy problem.·        By Chapter-5, they will know how to collect, clean, and preprocess relevant data.·        Using Chapter-6 and 8, they can implement a fair and unbiased ML model.·        Through Chapter-9 and 10, they can interpret results with statistical confidence.·        By Chapter-11, they will have the skills to write a publication-ready paper.In short, the book transforms a student project into publishable research.

Il giudizio non si delega. Il perimetro entro cui l'agente si muove, la verifica che deve passare, la condizione che lo ferma: quelli sì. Come un Senior trasforma vent'anni di mestiere nei vincoli che governano un agente, e come decisioni, criteri e lezioni restano quando la sessione finisce: è l'amplificazione del titolo.