Computer Programming/Artificial Intelligence/Python

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.

Learn Claude Code by building real projects. This hands-on companion turns the Claude Code Masterclass workshop into a practical self-paced guide for planning, coding, testing, reviewing, refactoring, and shipping software with AI.

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.

A vendor-neutral, mechanism-level field guide to operating and extending agentic coding harnesses (538 manuscript pages).

If you want to build real NLP applications instead of just experimenting with notebooks, spaCy is one of the best places to start. This book walks you through the entire journey from the fundamentals to advanced production workflows with practical explanations, real code examples and hands-on projects that show you how to build fast, reliable NLP systems for the real world.

PyTorch Deep Dive is a practical guide to mastering modern deep learning with PyTorch. From core concepts to advanced topics like transformers, diffusion models, and production deployment, it combines clear explanations, hands-on examples, and real-world best practices to help you build and scale AI applications with confidence.

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."

A hands-on guide for engineers and architects to build, optimize, and deploy scalable production-grade AI systems and LLM infrastructure.

Abandona el ensayo y error en la IA generativa. Un marco práctico y metodológico basado en el falsacionismo de Karl Popper para auditar, estresar y dominar la interacción con modelos de lenguaje.

Build powerful web applications with Python and Django.Django is one of the most capable frameworks for building modern web applications, but mastering it requires more than learning a few commands. You need to understand its architecture, database layer, request-response cycle, security model, APIs, testing practices, performance techniques, and deployment workflow.Django Unleashed: Building High-Performance Web Applications with Python provides a practical roadmap for developing Django applications from the ground up.Starting with Django fundamentals, you will learn how projects and applications are structured, how URLs connect requests to views, how templates generate dynamic interfaces, and how Django's ORM communicates with databases.The book then moves into models, QuerySets, relationships, forms, validation, authentication, authorization, static files, and media handling.A dedicated section on Django REST Framework introduces REST APIs, serializers, APIViews, ViewSets, routers, authentication, CRUD operations, filtering, pagination, and testing. You will also explore frontend integration using HTML, CSS, JavaScript, AJAX, React, and Vue.js.As your skills develop, the book introduces professional development practices including automated testing, CI/CD, security hardening, database optimization, caching, Redis, Memcached, Celery, profiling, and application scaling.The deployment chapters explain how to prepare Django applications for production and work with technologies such as Nginx, Gunicorn, HTTPS, AWS, DigitalOcean, and Heroku.With practical examples, troubleshooting guidance, real-world development concepts, and a comprehensive reference section, this book is designed to help you move from learning Django to building applications that are ready for real-world use.Learn Django. Build applications. Secure your code. Optimize performance. Deploy with confidence.

Teaser TextLearn AI by building real projects.Explore 10 practical beginner-level Artificial Intelligence projects and learn how to take an idea from problem definition to design, coding, testing, implementation, documentation, and future enhancement.From chatbots and face detection to resume screening, NLP, emotion detection, and intelligent recommendation systems, Vol-1 provides a structured introduction to practical AI development through the complete Software Development Life Cycle.Don’t just study AI. Build it.

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.

Artificial Intelligence is no longer a distant possibility—it is becoming a collaborative partner in education, research, software development, and professional decision-making.But how do frontier AI systems actually work?What makes safety-centered AI different from earlier generations of language models?How can students, researchers, educators, and professionals prepare for a future shaped by increasingly capable AI systems?In Claude 4 (Anthropic): Safety-First Frontier AI in 2026, author Anshuman Mishra presents a comprehensive and academically grounded exploration of one of the most influential frontier AI systems of the modern era.From Constitutional AI and advanced reasoning architectures to multimodal intelligence, agentic workflows, educational transformation, governance frameworks, workforce implications, and future AI research directions, this book provides readers with a balanced understanding of both opportunities and challenges.Rather than focusing on hype or speculation, the book emphasizes evidence-based analysis, responsible innovation, ethical deployment, and human-centered AI development.Whether you are a student seeking AI literacy, a researcher exploring frontier models, a professional adapting to technological change, or a policymaker shaping future governance frameworks, this book offers the knowledge needed to engage thoughtfully with the next generation of intelligent systems.The future of AI will not be determined by technology alone.It will be shaped by how responsibly humanity chooses to use it.

Teaser TextTake your AI projects to the next level.Explore 10 intermediate-level Artificial Intelligence projects covering NLP, Machine Learning, Computer Vision, prediction, classification, sentiment analysis, image recognition, and voice-based applications.From fake news detection and student performance prediction to resume ranking, plant disease identification, sign language recognition, and language translation, Vol-2 takes you deeper into practical AI development through a complete Software Development Life Cycle.Learn the concepts. Build the systems. Think like an AI developer.