Numéro d'article:
164768501
50 Algorithms Every Programmer Should Know: Tackle computer science challenges with classic to modern algorithms in machine learning software design
Numéro d'article:
164768501
MGA 287719
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Ce qui se démarque
Comprehensive Coverage
Covers essential algorithms from classic to modern, providing programmers with a well-rounded understanding of techniques across various domains like machine learning and cryptography.
Practical Applications
Focuses on real-world applications, helping programmers effectively tackle challenges in software design and data systems with proven algorithm solutions.
Up-to-Date Trends
Incorporates the latest advancements in algorithm development, ensuring readers are equipped with current knowledge relevant to today's technology landscape.
Détails du produit
- 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 overhaulPurchase of the print or Kindle book includes a free eBook in PDF format.Key FeaturesFamiliarize yourself with advanced deep learning architecturesExplore newer topics, such as handling hidden bias in data and algorithm explainabilityGet to grips with different programming algorithms and choose the right data structures for their optimal implementationBook DescriptionThe 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.What you will learnDesign algorithms for solving complex problemsBecome familiar with neural networks and deep learning techniquesExplore existing data structures and algorithms found in Python librariesImplement graph algorithms for fraud detection using network analysisDelve into state-of-the-art algorithms for proficient Natural Language Processing illustrated with real-world examplesCreate a recommendation engine that suggests relevant movies to subscribersGrasp the concepts of sequential machine learning models and their foundational role in the development of cutting-edge LLMsWho this book is forThis computer science book is for programmers or developers who want to understand the use of algorithms for problem-solving and writing efficient code.Whether you are a beginner looking to learn the most used algorithms concisely or an experienced programmer looking to explore cutting-edge algorithms in data science, machine learning, and cryptography, you'll find this book useful.Python programming experience is a must, knowledge of data science will be helpful but not necessary.Table of ContentsOverview of AlgorithmsData Structures Used in AlgorithmsSorting and Searching AlgorithmsDesigning AlgorithmsGraph AlgorithmsUnsupervised Machine Learning AlgorithmsTraditional Supervised Learning AlgorithmsNeural Network AlgorithmsAlgorithms for Natural Language ProcessingUnderstanding Sequential ModelsAdvanced Sequential Modeling AlgorithmsRecommendation EnginesAlgorithmic Strategies for Data HandlingCryptographyLarge-Scale AlgorithmsPractical Considerations
| Publisher | Packt Publishing |
| Publication date | 29 Sept. 2023 |
| Edition | 2. |
| Language | English |
| Print length | 538 pages |
| ISBN-10 | 1803247762 |
| ISBN-13 | 978-1803247762 |
| Dimensions | 19.05 x 3.1 x 23.5 cm |
À qui est-ce destiné ?
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Aspiring Programmers
Beginner coders will find foundational algorithms indispensable for understanding core programming concepts and practices.
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Data Scientists
Professionals in data science can benefit from insights into algorithms specific to machine learning and data systems.
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Cryptography Enthusiasts
This book provides valuable information on modern algorithms vital for anyone interested in cryptography and secure communications.
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Complete Beginners
Those with no programming experience may struggle to comprehend the complex algorithms without prior knowledge.
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English edition Imran Ahmad Format: Paperback Editorial Review
50 Algorithms Every Programmer Should Know: Tackle Computer Science Challenges With Classic To Modern Algorithms In Machine Learning Software Design Data Systems And Cryptography is a comprehensive resource by Dr. Imran Ahmad, offering structured knowledge on essential algorithms for both novice and seasoned programmers. The book begins with fundamental concepts like sorting and searching algorithms, progressing to advanced topics including machine learning and cryptography, emphasizing practical application through Python code snippets and real-world examples. Despite its strengths, some readers noted inconsistencies in explanations and code, indicating a need for careful proofreading. Overall, this book serves as a valuable guide in understanding and applying algorithms effectively.
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Avantages
- Well-structured content for beginners and experienced programmers
- Practical examples and Python code snippets
- Covers a broad range of algorithms
- Addresses ethical considerations in algorithmic solutions
- Includes advanced topics in data handling and AI
Les inconvénients
- Some explanations lack depth or clarity in places
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MGA 287719
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