50 Algorithms Every Programmer Should Know: Tackle computer science challenges with classic to modern algorithms in machine learning, software design, data systems, and cryptography
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50 Algorithms Every Programmer Should Know: Tackle computer science challenges with classic to modern algorithms in machine learning, software design, data systems, and cryptography
Delve into the realm of generative AI and large language models (LLMs) while exploring modern deep learning techniques, including LSTMs, GRUs, RNNs with new chapters included in this 50% new edition
50 Algorithms Every Programmer Should Know: Tackle computer science challenges with classic to modern algorithms in machine learning, software design, data systems, and cryptography
товар №: 83887564

50 Algorithms Every Programmer Should Know: Tackle computer science challenges with classic to modern algorithms in machine learning, software

90% of respondents would recommend this to a friend

товар №: 83887564

KZT 34536

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Delve into the realm of generative AI and large language models (LLMs) while exploring modern deep learning techniques, including LSTMs, GRUs, RNNs with new chapters included in this 50% new edition
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What Stands Out

Comprehensive Coverage
Offers a wide range of algorithms, from classic to contemporary, providing programmers with essential knowledge across various areas like machine learning and cryptography for tackling diverse challenges.
Practical Application
Focuses on real-world applications of algorithms, enhancing problem-solving skills that are directly applicable to software design and data systems, making it an invaluable resource for developers.
Updated Content
Released in 2023, this book includes the latest advancements in algorithmic techniques, ensuring that programmers stay relevant and competitive in a rapidly evolving tech landscape.

Информация о продукте

Shop 50 Algorithms Every Programmer Should Know: Tackle computer science challenges with classic to modern algorithms in machine learning, software design, data systems, and cryptography online at a best price in Kazakhstan. 1803247762
  • Explore advanced deep learning architectures and modern deep learning techniques
  • Learn different programming algorithms and choose the right data structures
  • Examine linear programming, page ranking, and graph algorithms, as well as machine learning algorithms
  • Understand the math and logic behind deep learning models, including Large Language Models (LLMs) and sequential models
  • Develop skills in applying algorithms for computational problems and implementing parallel processing techniques
  • Designed for programmers seeking to understand and use algorithms for problem-solving and efficient code writing
Publisher Packt Publishing
Publication date 29 Sept. 2023
Edition 2nd
Language English
Print length 538 pages
ISBN-10 1803247762
ISBN-13 978-1803247762
Item weight 912 g
Dimensions 19.05 x 3.1 x 23.5 cm

Who Should Buy?

Suitable For
  • Aspiring Programmers

    Beginners seeking a comprehensive understanding of algorithms to kickstart their programming career will find this beneficial.

  • Students in CS

    Computer science students needing a solid resource to supplement their coursework and better grasp algorithms concepts.

  • Software Developers

    Experienced developers wanting to refine their skills, explore modern algorithms, and improve their problem-solving capabilities.

Not Suitable For
  • Casual Readers

    Individuals looking for light reading or casual information would find the technical content challenging and unengaging.

ОПИСАНИЕ ТОВАРА

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Вопросы и ответы клиентов

  • вопрос: What topics are covered in this book?

    отвечать: The book covers topics such as neural networks, deep learning, graph algorithms, machine learning applications, natural language processing, recommendation systems, cryptography, and parallel processing techniques.
  • вопрос: What approach does this book take?

    отвечать: The book strikes a balance between helping readers select and use algorithms to solve real-world problems and explaining the logic behind them for a deeper understanding. It starts with an introduction to algorithms and progresses to more advanced concepts.
  • вопрос: What is the author's background?

    отвечать: The author has a rich background in cloud computing, AI, and machine learning. They have worked on high-profile projects, taught at Google, and are a visiting professor at Carleton University.

Software Design Editorial Review

50 Algorithms Every Programmer Should Know is a comprehensive guide to algorithms and data structures aimed at enhancing your programming skills. Published by Packt Publishing on 29 Sept. 2023, the second edition updates content on techniques from machine learning to cryptography. Readers praise the clear explanations and application case studies that link theoretical knowledge with real-world problems. One reviewer noted how it revived memories of using searching algorithms back in college, showcasing its ability to connect past concepts to modern applications. Additionally, its practical approach and coverage of core concepts make it an invaluable resource for both novice and experienced programmers alike.

Customer Reviews & Ratings

93 оценки клиентов
  • 5 звезда
    77%
  • 4 звезда
    14%
  • 3 звезда
    4%
  • 2 звезда
    1%
  • 1 звезда
    4%

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Плюсы

  • Covers both basic and advanced algorithms comprehensively
  • Includes practical case studies for real-world application
  • Accessible explanations for complex topics like cryptography
  • Updated content on generative AI enhances relevance
  • Clear structure aids learning for beginners and pros

Минусы

  • Mix of content may confuse some readers about the target audience

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KZT 34536

Закажите сейчас и получите товар приблизительно Пятница, Октябрь 09

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Особенности и преимущества

  • Explore modern deep learning techniques
  • Learn about generative AI and large language models
  • Includes new chapters on LSTMs, GRUs, RNNs
  • 50% new edition with updated algorithms
  • Addresses hidden data biases and demystifies algorithm explainability

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