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Category: "Computer Programming/Artificial Intelligence/Python"

Computer Programming/Artificial Intelligence/Python

  1. Deep Learning with Python: From Fundamentals to Frontiers
    Deep Learning with Python: From Fundamentals to Frontiers
    A Complete Guide to Building, Training, and Deploying Neural Networks
    Steve Publications

    Deep learning is transforming the world, and this book provides a clear, practical path to mastering it. Through concise explanations and hands-on Python examples, you will learn to build, train, optimize, and deploy neural networks with confidence for real-world applications.

  2. PyTorch Deep Dive
    PyTorch Deep Dive
    From Foundations to Production: A Complete Guide to Modern Deep Learning
    Steve Publications

    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.

  3. Python Under Pressure
    Python Under Pressure
    A Complete Interview Guide — written from the interviewer's side of the table.
    Ahmed

    The Python interview guide written from the interviewer's side of the table. 35 chapters. Every benchmark measured. Every line of code verified. What senior engineers actually get asked — and what separates the ones who get the offer.

  4. Web Programming With Python and Flask: A Comprehensive Guide

    Web Programming with Python and Flask: A Comprehensive Guide provides a structured and practical pathway into modern web development using one of Python’s most flexible and developer-friendly frameworks.Beginning with the fundamentals of web programming, the book guides readers through the complete Flask application-development journey—from installing Python and creating a development environment

  5. Advanced Prompt Engineering for LLMs
    Advanced Prompt Engineering for LLMs
    Concepts algorithms and applications for bca mca & professionals
    Anshuman Mishra

    Advanced Prompt Engineering for LLMs: 2026 Techniques That Actually Deliver Results takes readers beyond basic instructions and introduces a complete system for working with modern Large Language Models.Discover how to:• Apply powerful frameworks such as RACE and TREE • Build advanced multi-layer prompts • Use meta-prompting to create and improve prompts • Design specialized expert personas

  6. THE ARCHITECTURE OF THOUGHT Applied Mathematics in Large Language Models & GenAI
    THE ARCHITECTURE OF THOUGHT Applied Mathematics in Large Language Models & GenAI
    Applied mathematics in large language Models &GenAI
    AhmedAdawy

    Move beyond the API. Dismantle the AI black box and build generative engines from scratch with pure Python and NumPy. Master the profound geometric principles and applied mathematics driving LLMs and Transformers. Transform from a mere consumer into an elite AI innovator by writing the core mathematical architecture yourself—no shortcuts, no frameworks, just pure engineering excellence.

  7. DSPy in Depth
    DSPy in Depth
    Programming Language Models from Zero to Production
    Steve Publications

    Learn to build production-ready LLM applications with DSPy through hands-on tutorials, complete runnable examples, and real-world projects. Master DSPy's core abstractions and create AI systems that improve with data instead of endless prompt tweaking.

  8. AI Without Mathematics
    AI Without Mathematics
    A Practical Guide to Understanding LLMs, RAG, AI Agents, and Modern AI Systems Without Starting from Equations
    Britto

    A practical, systems-first guide to understanding LLMs, RAG, AI agents, GraphRAG, evaluation, fine-tuning, and modern AI applications — without needing to start with equations.

  9. Kubernetes AI
    Kubernetes AI
    Run LLMs, GPUs, and ML Workloads in Production
    Luca Berton

    Build and operate production AI platforms on Kubernetes. Learn to manage NVIDIA GPUs, serve and optimize LLMs with vLLM, run training and batch workloads, and design secure, observable, multi-tenant infrastructure for AI at scale.

  10. The Model Context Protocol (MCP) in Practice
    The Model Context Protocol (MCP) in Practice
    Building, Integrating, and Scaling Custom Tool Servers for AI Agents
    Yohan Rodriguez

    A hands-on guide to designing, building, testing, and deploying secure stdio and SSE MCP servers in Python and TypeScript (447 manuscript pages).

  11. Linear Programming and AI Optimization Models VOL-3
    Linear Programming and AI Optimization Models VOL-3
    Foundations Algorithms and Modern Applications in Operations Research and Machine Learning
    Anshuman Mishra

    Linear Programming and AI Optimization Models (VOL-3) delivers practical mastery in scheduling, supply chain, logistics, hybrid AI-OR systems, large-scale cloud optimization, and emerging technologies. With Python implementations, industry case studies, and forward-looking research trends, this volume turns theory into powerful real-world solutions.

  12. Linear Programming and AI Optimization Models VOL-2
    Linear Programming and AI Optimization Models VOL-2
    Foundations Algorithms and Modern Applications in Operations Research and Machine Learning
    Anshuman Mishra

    Take your optimization skills to the next level with AI.Linear Programming and AI Optimization Models (VOL-2) dives deep into the algorithms driving modern Machine Learning and Intelligent Systems. Master Gradient Descent, Adam, Reinforcement Learning, Genetic Algorithms, Particle Swarm Optimization, Constraint Satisfaction, and advanced Network Models.

  13. LLM Quantization
    LLM Quantization
    From the Bits Up
    Hatem M.

    Anyone can run INT4 and read off the accuracy drop. This book explains why that number is what it is — building every quantization method from scratch, breaking it on purpose, and measuring the result. Quantization, from the bits up.

  14. AI & LLMs from Scratch
    AI & LLMs from Scratch
    Build Production-Ready AI Tools with Python for Modern AI Careers
    A.P. Pyre

    Build real-world AI applications with Python—not just demos. Learn LLM APIs, RAG, embeddings, vector search, AI agents, prompt engineering, security, deployment, and production-ready architectures through practical projects and expert guidance. Gain the skills to build, ship, and scale modern AI systems with confidence.

  15. Python For Beginners : A Step by Step Guide

    Learn Python from scratch with this clear, step-by-step beginner’s guide. Perfect for students, professionals, and self-learners. Master programming fundamentals through practical examples, exercises, and real mini-projects. Build confidence and start coding today!