À propos de ce livre

The ability to use algorithms to solve real-world problems is a must-have skill for any developer or programmer. This book will help you not only to develop the skills to select and use an algorithm to tackle problems in the real world but also to understand how it works.

You'll start with an introduction to algorithms and discover various algorithm design techniques, before exploring how to implement different types of algorithms, with the help of practical examples. As you advance, you'll learn about linear programming, page ranking, and graphs, and will then work with machine learning algorithms to understand the math and logic behind them.

Case studies will show you how to apply these algorithms optimally before you focus on deep learning algorithms and learn about different types of deep learning models along with their practical use.

You will also learn about modern sequential models and their variants, algorithms, methodologies, and architectures that are used to implement Large Language Models (LLMs) such as ChatGPT.

Finally, you'll become well versed in techniques that enable parallel processing, giving you the ability to use these algorithms for compute-intensive tasks.

By the end of this programming book, you'll have become adept at solving real-world computational problems by using a wide range of algorithms.

Commencez ce livre dès aujourd'hui pour 0 €

  • Accédez à tous les livres de l'app pendant la période d'essai
  • Sans engagement, annulez à tout moment
Essayer gratuitement
Plus de 52 000 personnes ont noté Nextory 5 étoiles sur l'App Store et Google Play.

D'autres ont aimé

  1. Automated Workflows with n8n : Definitive Reference for Developers and Engineers

    Richard Johnson

  2. Python for Finance : Apply powerful finance models and quantitative analysis with Python

    Yuxing Yan

  3. Accelerating DevSecOps on AWS : Create secure CI/CD pipelines using Chaos and AIOps

    Nikit Swaraj

  4. Building LLM Powered Applications : Create intelligent apps and agents with large language models

    Valentina Alto

  5. Building AI Agents with LLMs, RAG, and Knowledge Graphs : A practical guide to autonomous and modern AI agents

    Salvatore Raieli, Gabriele Iuculano

  6. 1.0

    Unlocking Data with Generative AI and RAG : Learn AI agent fundamentals with RAG-powered memory, graph-based RAG, and intelligent recall

    Keith Bourne

  7. Learn PostgreSQL : Use, manage, and build secure and scalable databases with PostgreSQL 16

    Luca Ferrari, Enrico Pirozzi

  8. Microsoft Copilot in Azure : AI-powered cloud automation and optimization

    David Rendón, Steve Miles

  9. Getting Started with Forex Trading Using Python : Beginner's guide to the currency market and development of trading algorithms

    Alex Krishtop

  10. 5.0

    RAG-Driven Generative AI : Build custom retrieval augmented generation pipelines with LlamaIndex, Deep Lake, and Pinecone

    Denis Rothman

  11. Building Natural Language and LLM Pipelines : Build production-grade RAG, tool contracts, and context engineering with Haystack and LangGraph

    Laura Funderburk

  12. Generative AI on Google Cloud with LangChain : Design scalable generative AI solutions with Python, LangChain, and Vertex AI on Google Cloud

    Leonid Kuligin, Jorge Zaldívar, Maximilian Tschochohei

Livres similaires