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Artikel #:
83887564
50 Algorithms Every Programmer Should Know: Tackle computer science challenges with classic to modern algorithms in machine learning, software
88% of respondents would recommend this to a friend
Artikel #:
83887564
€ 59
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Naročite zdaj in dobite okoli dne: Torek, Oktober 13
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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.
Podrobnosti produkta
- 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?
-
Aspiring Programmers
Beginners seeking a comprehensive understanding of algorithms to kickstart their programming career will find this beneficial.
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Students in CS
Computer science students needing a solid resource to supplement their coursework and better grasp algorithms concepts.
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Software Developers
Experienced developers wanting to refine their skills, explore modern algorithms, and improve their problem-solving capabilities.
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Casual Readers
Individuals looking for light reading or casual information would find the technical content challenging and unengaging.
OPIS IZDELKA
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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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.
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Prednosti
- 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
Slabosti
- Mix of content may confuse some readers about the target audience
Product Price History
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Naročite zdaj in dobite okoli dne: Torek, Oktober 13
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Značilnosti in prednosti
- 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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