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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
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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
Product Details
- 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?
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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.
Product Description
Customer Questions & Answers
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Question:
What topics are covered in this book?
Answer: 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. -
Question:
What approach does this book take?
Answer: 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. -
Question:
What is the author's background?
Answer: 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
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Pros
- 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
Cons
- Mix of content may confuse some readers about the target audience
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STD 1592965
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Features & Benefits
- 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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