Computer Programming/Artificial Intelligence/Python

Master DeepSeek V3 — one of the most capable AI models of its time.This practical guide teaches students, researchers, and professionals how to use DeepSeek V3 for learning, research, coding, content creation, automation, and productivity — with strong focus on prompt engineering and responsible AI usage.

How does code actually run under the hood? Stop guessing and master the hidden physics of execution. Learn how Python and Java truly manage memory, layout data structures, and drive high-performance algorithms.

A practical, code-first guide to physics-informed machine learning for scientists and engineers. You'll build a working Physics-Informed Neural Network from scratch in PyTorch, solve a real differential equation, and verify it against the exact solution — staying honest about both the power and the limits of the method.

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.

Threat modeling is broken. It takes days, costs thousands, and most teams skip it entirely. What if your AI coding assistant could do it for you — systematically, consistently, and in minutes? This book shows you how to build an MCP server that makes it happen. You'll create 80+ structured tools that guide any AI assistant through a rigorous 9-phase STRIDE threat modeling workflow. Not vague prompts that produce unstructured text — real, typed, validated tools that build up a complete threat model piece by piece: business context, architecture, threat actors, trust boundaries, data flows, STRIDE-based threats, mitigations, and a final JSON export compatible with AWS Threat Composer. **What you'll build:** - A full MCP server with FastMCP (stdio + SSE transport) - Pydantic v2 data models for type-safe threat modeling - Case-insensitive enum validation (because AI isn't always consistent) - 11 tool modules covering every phase of STRIDE analysis - Customizable organization security guidelines loaded from `.md` files - Docker deployment for team-wide access - Compliance gap analysis that validates against mandatory controls - A complete workflow orchestrator with progress tracking **What makes this different:** The server doesn't call any LLM itself. It provides the structure and tools — your AI assistant (Claude, Kiro, Cursor, Copilot) provides the intelligence. This means it works with any model, any provider, forever. No API keys, no token costs for the server itself. **Who this is for:** - Security engineers who want to automate repetitive threat modeling - Python developers building MCP servers for any domain - DevSecOps teams embedding security into AI-assisted workflows - Architects who need consistent, auditable threat models - Anyone curious about how MCP tools work under the hood **By the end of this book**, you'll have a production-ready MCP server, a deep understanding of how AI tools are structured, and transferable patterns for building MCP servers in any domain — not just security.

Have you ever wondered how AI knows that "Which company designs iPhone?" is best answered by "Apple designs iPhone" — and not "I love to eat apple" or "Both Apple and Orange are fruits"? This book takes you on a visual, step-by-step journey to discover how artificial intelligence reads the meaning behind words — not just the words themselves. By the end, you'll understand the elegant idea powering modern AI chatbots, and write your own Python programs to find the best answer to any question from a list of sentences.

# 🚀 Master the Math Behind Artificial Intelligence!Stop drowning in complex textbooks. This premium, high-density **AI Math Cheat Sheet** is engineered specifically for Data Scientists, ML Engineers, and Python Developers who want to bridge the gap between mathematical theory and production-ready co

A practical guide to operating a fleet of AI coding agents through routing, memory, skills, MCP, guardrails, and a persistent control plane (322 manuscript pages).

Stop guessing the math behind AI and start coding it. This practical guide bridges the gap between complex formulas and real-world Python implementation, giving you the exact blueprint to master the algorithms powering modern machine learning.

You have built an AI agent that works beautifully in a demo, then falls apart the moment real users arrive: it invents answers, burns through tokens, and freezes on slow tools. The problem was never your prompt. This book shows you the real fix, layer by layer, and turns "I hope my agent works" into "I can prove it does."

Want to learn Python from the ground up and master its real-world applications?Python Programming: Basics to Advanced Concepts is your complete guide to one of the world's most powerful and versatile programming languages. Whether you are a BCA or MCA student, an aspiring software developer, a competitive examination candidate, or a technology enthusiast, this book provides a structured learning path from Python fundamentals to advanced programming techniques.Inside this book, you will learn:✔ Python syntax, variables, data types, and operators✔ Conditional statements, loops, and functions✔ Lists, tuples, dictionaries, sets, and strings✔ Object-Oriented Programming (OOP)✔ Exception handling and file management✔ Modules, packages, generators, and decorators✔ Database programming with SQLite and MySQL✔ GUI development using Tkinter✔ Web development with Flask and Django✔ Data analysis using NumPy and Pandas✔ Machine Learning fundamentals with Python✔ Network programming and cybersecurity applications✔ Testing, debugging, and performance optimization✔ End-to-end Python project developmentThe book combines academic rigor with practical learning, offering clear explanations, coding examples, exercises, and real-world applications throughout every chapter.Whether your goal is to excel in university examinations, prepare for interviews, build software projects, or launch a professional programming career, this book provides the knowledge, skills, and confidence required to become a proficient Python developer.Start your Python journey today and unlock opportunities in software development, data science, artificial intelligence, cybersecurity, automation, and beyond.

Mastering Deep Learning with PyTorch: From Fundamentals to Real-World Projects This first edition delivers a complete end-to-end learning pathway for mastering modern deep learning using PyTorch. Major Topics Covered • Deep Learning Fundamentals• Artificial Neural Networks• PyTorch Framework and Tensor Operations• Automatic Differentiation (Autograd)• Feedforward Neural Networks• Convolutional Neural Networks (CNNs)• Recurrent Neural Networks (RNNs)• Long Short-Term Memory Networks (LSTMs)• Attention Mechanisms• Transformer Architectures• Hugging Face Ecosystem• Generative Adversarial Networks (GANs)• Computer Vision Applications• Natural Language Processing Applications• Model Evaluation and Optimization• Hyperparameter Tuning• Explainable Artificial Intelligence (XAI)• Ethical AI and Bias Mitigation• Model Deployment and Production Pipelines Practical Implementations Included • Image Classification Systems• Object Detection Models• Image Segmentation Applications• Text Classification Systems• Sentiment Analysis Models• Language Translation Pipelines• Transformer-Based NLP Applications• GAN-Based Image Generation Capstone Projects Project 1: Pneumonia Detection using CNNProject 2: Sentiment Analysis using LSTMProject 3: Image Colorization using GANProject 4: Real-Time Object Detection SystemProject 5: Transformer-Based Intelligent Chatbot Industry Tools and Technologies • PyTorch• TorchVision• Hugging Face Transformers• TensorBoard• Flask• ONNX• Docker Concepts• AWS Deployment Basics• Google Cloud Deployment Concepts Intended Audience • Undergraduate Students• Postgraduate Students• Data Scientists• Machine Learning Engineers• AI Researchers• Software Developers• Academic Professionals• Industry Practitioners Learning Outcomes Upon completion of this book, readers will be able to:• Design and train neural network architectures.• Build computer vision applications using CNNs.• Develop NLP solutions using RNNs, LSTMs, and Transformers.• Implement generative AI systems using GANs.• Evaluate and optimize deep learning models.• Deploy PyTorch models into production environments.• Understand ethical considerations in AI development.• Create portfolio-ready deep learning projects.This release establishes a strong foundation for academic learning, industrial applications, and advanced research in modern deep learning.

Learn Machine Learning. Build Real Projects. Launch Your AI Career.Machine Learning is transforming the world—and Python is the language powering that revolution.Mastering Machine Learning with Python: From Beginner to Pro provides a complete roadmap for understanding, implementing, and deploying modern machine learning solutions.Inside this book, you'll discover:✔ Artificial Intelligence and Machine Learning Fundamentals✔ Data Preprocessing and Feature Engineering✔ Python for Machine Learning✔ Regression and Classification Algorithms✔ Clustering and Dimensionality Reduction✔ Model Evaluation and Hyperparameter Tuning✔ Ensemble Learning Techniques✔ Neural Networks and Deep Learning✔ TensorFlow and Keras Development✔ Real-World Machine Learning Projects✔ Flask and Streamlit Deployment✔ Introduction to MLOps and Production AIFrom your first machine learning model to deploying intelligent applications, this book delivers the practical knowledge and hands-on experience needed to become an AI and Machine Learning professional.Whether you're a student, developer, data analyst, researcher, or career changer, this book will help you transform data into intelligent solutions and ideas into impactful applications.

Learn Python. Build AI. Create the Future.What if you could write Python programs that generate content, answer questions, create code, summarize documents, and power intelligent applications?Python Simplified with Generative AI takes you on a complete journey from Python basics to advanced AI-powered development.Inside this book, you will learn:✔ Python Programming from Scratch✔ Data Structures and Object-Oriented Programming✔ AI and Machine Learning Foundations✔ Generative AI Concepts and Applications✔ Prompt Engineering Techniques✔ GPT-Powered Text Generation✔ AI Chatbots and Virtual Assistants✔ Image Generation with AI APIs✔ Flask, FastAPI, Streamlit, and Gradio Development✔ Real-World AI Projects for Your PortfolioWhether you are a student, professional developer, freelancer, educator, or entrepreneur, this book will help you transform ideas into intelligent applications and prepare for the next generation of software development.The future belongs to developers who can combine programming with artificial intelligence. Start building that future today.