50 Algorithms Every Programmer Should Know

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Key FeaturesDiscussion on Advanced Deep Learning ArchitecturesNew chapters on sequential models explaining modern deep learning techniques, like LSTMs, GRUs, and RNNs and Large Language Models (LLMs)Explore newer topics, such as how to handle hidden bias in data and the explainability of the algorithmsGet to grips with different programming algorithms and choose the right data structures for their optimal implementation
Book Description
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 by understanding 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 even 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 will 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 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 analysisUse machine learning algorithms to process Twitter data in real timeCreate a recommendation engine that suggests relevant movies to subscribersImplement security using symmetric and asymmetric encryption on Google Cloud Platform
Who This Book Is For
This 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 ContentsCore AlgorithmsData StructuresSorting and Searching AlgorithmsDesigning AlgorithmsGraph AlgorithmsUnsupervised Machine Learning AlgorithmsSupervised Learning AlgorithmsNeural Network AlgorithmsNatural Language ProcessingSequential ModelsAdvanced Machine Learning ModelsRecommendation EnginesCryptographyLarge-Scale AlgorithmsEvaluating Algorithmic SolutionsPractical Considerations


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