Books like 'Literate Programming'
Readers who enjoyed Literate Programming by Donald Ervin Knuth also liked the following books featuring the same tropes, story themes, relationship dynamics and character types.
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Web Scalability for Startup Engineers by Artur Ejsmont
Rated: 4.50 of 5 stars · 6 ratingsPublisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product.Design and build scalable web applications quicklyThis is an invaluable roadmap for meeting the rapid demand to deliver scalable applications in a startup environment... -
![Aws Solutions Architect Associate Sg by Joe Baron, Hisham Baz]()
Aws Solutions Architect Associate Sg by Joe Baron, Hisham Baz
Rated: 4.17 of 5 stars · 6 ratingsValidate your AWS skills. This is your opportunity to take the next step in your career by expanding and validating your skills on the AWS cloud... -
![I Heart Logs by Jay Kreps]()
I Heart Logs by Jay Kreps
Rated: 3.83 of 5 stars · 6 ratingsWhy would someone write a book about computer logs? It turns out that the humble log is an abstraction that lies at the heart of many systems, from NoSQL databases to cryptocurrencies. Yet other than occasionally tailing a log file, most engineers don't think much about them. This book shows you why logs are worthy of your attention... -
![Designing Data-Intensive Applications by Martin Kleppmann]()
Designing Data-Intensive Applications by Martin Kleppmann
Rated: 4.72 of 5 stars · 18 ratingsData is at the center of many challenges in system design today. Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and maintainability. In addition, we have an overwhelming variety of tools, including relational databases, NoSQL datastores, stream or batch processors, and message brokers... -
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![Hands-On Machine Learning with Scikit-Learn and TensorFlow by Aurélien Géron]()
Hands-On Machine Learning with Scikit-Learn and TensorFlow by Aurélien Géron
Rated: 4.57 of 5 stars · 14 ratingsA series of Deep Learning breakthroughs have boosted the whole field of machine learning over the last decade. Now that machine learning is thriving, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how... -
![C Programming Language by Ritchie Kernighan, Dennis M. Ritchie]()
C Programming Language by Ritchie Kernighan, Dennis M. Ritchie
Rated: 4.45 of 5 stars · 20 ratingsClassic, bestselling introduction that teaches the language and illustrates useful algorithms, data structures and programming techniques... -
![Structure and Interpretation of Computer Programs by Harold Abelson, Gerald Jay Sussman]()
Structure and Interpretation of Computer Programs by Harold Abelson, Gerald Jay Sussman
Rated: 4.44 of 5 stars · 18 ratingsStructure and Interpretation of Computer Programs has had a dramatic impact on computer science curricula over the past decade. This long-awaited revision contains changes throughout the text... -
![Code: The Hidden Language of Computer Hardware and Software by Charles Petzold]()
Code: The Hidden Language of Computer Hardware and Software by Charles Petzold
Rated: 4.38 of 5 stars · 21 ratingsWhat do flashlights, the British invasion, black cats, and seesaws have to do with computers? In CODE, they show us the ingenious ways we manipulate language and invent new means of communicating with each other. And through CODE, we see how this ingenuity and our very human compulsion to communicate have driven the technological innovations of the past two centuries... -
![R for Data Science: Import, Tidy, Transform, Visualize, and Model Data by Hadley Wickham, Garrett Grolemund]()
R for Data Science: Import, Tidy, Transform, Visualize, and Model Data by Hadley Wickham, Garrett Grolemund
Rated: 4.60 of 5 stars · 10 ratingsLearn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible... -
![Deep Learning with Python by François Chollet]()
Deep Learning with Python by François Chollet
Rated: 4.60 of 5 stars · 10 ratingsDeep learning is applicable to a widening range of artificial intelligence problems, such as image classification, speech recognition, text classification, question answering, text-to-speech, and optical character recognition. It is the technology behind photo tagging systems at Facebook and Google, self-driving cars, speech recognition systems on your smartphone, and much more... -
![The Visual Display of Quantitative Information by Edward R. Tufte]()
The Visual Display of Quantitative Information by Edward R. Tufte
Rated: 4.39 of 5 stars · 18 ratingsThe classic book on statistical graphics, charts, tables. Theory and practice in the design of data graphics, 250 illustrations of the best (and a few of the worst) statistical graphics, with detailed analysis of how to display data for precise, effective, quick analysis. Design of the high-resolution displays, small multiples. Editing and improving graphics. The data-ink ratio... -
![Google必修的圖表簡報術 by 柯爾・諾瑟鮑姆・娜菲克]()
Google必修的圖表簡報術 by 柯爾・諾瑟鮑姆・娜菲克
Rated: 4.39 of 5 stars · 18 ratingsDon't simply show your data--tell a story with it! "Storytelling with Data" teaches you the fundamentals of data visualization and how to communicate effectively with data. You'll discover the power of storytelling and the way to make data a pivotal point in your story... -
![Clean Code: A Handbook of Agile Software Craftsmanship by Robert C. Martin]()
Clean Code: A Handbook of Agile Software Craftsmanship by Robert C. Martin
Rated: 4.32 of 5 stars · 25 ratingsEven bad code can function. But if code isn't clean, it can bring a development organization to its knees. Every year, countless hours and significant resources are lost because of poorly written code. But it doesn't have to be that way. Noted software expert Robert C. Martin presents a revolutionary paradigm with Clean Code: A Handbook of Agile Software Craftsmanship... -
![The Pragmatic Programmer: From Journeyman to Master by Andy Hunt, Dave Thomas]()
The Pragmatic Programmer: From Journeyman to Master by Andy Hunt, Dave Thomas
Rated: 4.32 of 5 stars · 25 ratingsStraight from the programming trenches, The Pragmatic Programmer cuts through the increasing specialization and technicalities of modern software development to examine the core process--taking a requirement and producing working, maintainable code that delights its users... -
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![The Elements of Statistical Learning: Data Mining, Inference, and Prediction by Trevor Hastie, Robert Tibshirani]()
The Elements of Statistical Learning: Data Mining, Inference, and Prediction by Trevor Hastie, Robert Tibshirani
Rated: 4.43 of 5 stars · 14 ratingsThis book describes the important ideas in a variety of fields such as medicine, biology, finance, and marketing in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of colour graphics... -
![The AI Revolution: The Road to Superintelligence by Tim Urban]()
The AI Revolution: The Road to Superintelligence by Tim Urban
Rated: 4.63 of 5 stars · 8 ratingsThe topic everyone in the world should be talking about... -
![Grokking Algorithms: An illustrated guide for programmers and other curious people by Aditya Bhargava, Manning Publications by Aditya Y. Bhargava]()
Grokking Algorithms: An illustrated guide for programmers and other curious people by Aditya Bhargava, Manning Publications by Aditya Y. Bhargava
Rated: 4.38 of 5 stars · 16 ratingsSummary Grokking Algorithms is a fully illustrated, friendly guide that teaches you how to apply common algorithms to the practical problems you face every day as a programmer. You'll start with sorting and searching and, as you build up your skills in thinking algorithmically, you'll tackle more ...Available here : readmeaway... -
![The DevOps Handbook, Second Edition: How to Create World-Class Agility, Reliability, & Security in Technology Organizations by Gene Kim, Jez Humble]()
The DevOps Handbook, Second Edition: How to Create World-Class Agility, Reliability, & Security in Technology Organizations by Gene Kim, Jez Humble
Rated: 4.33 of 5 stars · 18 ratingsThis award-winning and bestselling business handbook for digital transformation is now fully updated and expanded with the latest research and new case studies!Over the last five years, The DevOps Handbook has been the definitive guide for taking the successes laid out in the bestselling The Phoenix Project and applying them in any organization... -
![Artificial Intelligence: A Guide for Thinking Humans by Melanie Mitchell, Мелани Митчелл]()
Artificial Intelligence: A Guide for Thinking Humans by Melanie Mitchell, Мелани Митчелл
Rated: 4.42 of 5 stars · 12 ratingsNo recent scientific enterprise has proved as alluring, terrifying, and filled with extravagant promise and frustrating setbacks as artificial intelligence. The award-winning author Melanie Mitchell, a leading computer scientist, now reveals AI’s turbulent history and the recent spate of apparent successes, grand hopes, and emerging fears surrounding it... -
![The Art of Computer Programming, Volume 1: Fundamental Algorithms by Donald Ervin Knuth]()
The Art of Computer Programming, Volume 1: Fundamental Algorithms by Donald Ervin Knuth
Rated: 4.36 of 5 stars · 14 ratingsThe bible of all fundamental algorithms and the work that taught many of today's software developers most of what they know about computer programming. -Byte, September 1995 I can't begin to tell you how many pleasurable hours of study and recreation they have afforded me! I have pored over them in cars, restaurants, at work, at home.. -
![The Algorithm Design Manual by Steven S. Skiena]()
The Algorithm Design Manual by Steven S. Skiena
Rated: 4.36 of 5 stars · 14 ratingsMost professional programmers that I've encountered are not well prepared to tacklealgorithmdesignproblems.Thisisapity, becausethetechniquesofalgorithm design form one of the core practical technologies of computer science... -
![The Alignment Problem: Machine Learning and Human Values by Brian Christian]()
The Alignment Problem: Machine Learning and Human Values by Brian Christian
Rated: 4.31 of 5 stars · 16 ratingsA jaw-dropping exploration of everything that goes wrong when we build AI systems and the movement to fix them. Today’s "machine-learning" systems, trained by data, are so effective that we’ve invited them to see and hear for us—and to make decisions on our behalf. But alarm bells are ringing. Recent years have seen an eruption of concern as the field of machine learning advances... -
![Refactoring: Improving the Design of Existing Code by Martin Fowler, Kent Beck]()
Refactoring: Improving the Design of Existing Code by Martin Fowler, Kent Beck
Rated: 4.28 of 5 stars · 18 ratingsAs the application of object technology—particularly the Java programming language—has become commonplace, a new problem has emerged to confront the software development community. Significant numbers of poorly designed programs have been created by less-experienced developers, resulting in applications that are inefficient and hard to maintain and extend... -
![Reinforcement Learning: An Introduction by Richard S. Sutton, Andrew G. Barto]()
Reinforcement Learning: An Introduction by Richard S. Sutton, Andrew G. Barto
Rated: 4.50 of 5 stars · 8 ratingsRichard Sutton and Andrew Barto provide a clear and simple account of the key ideas and algorithms of reinforcement learning. Their discussion ranges from the history of the field's intellectual foundations to the most recent developments and applications... -
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![Information Theory, Inference and Learning Algorithms by David J.C. MacKay]()
Information Theory, Inference and Learning Algorithms by David J.C. MacKay
Rated: 4.50 of 5 stars · 8 ratingsInformation theory and inference, often taught separately, are here united in one entertaining textbook. These topics lie at the heart of many exciting areas of contemporary science and engineering - communication, signal processing, data mining, machine learning, pattern recognition, computational neuroscience, bioinformatics, and cryptography... -
![Code Complete by Steve McConnell]()
Code Complete by Steve McConnell
Rated: 4.25 of 5 stars · 20 ratingsWidely considered one of the best practical guides to programming, Steve McConnell's original CODE COMPLETE has been helping developers write better software for more than a decade. Now this classic book has been fully updated and revised with leading-edge practices--and hundreds of new code samples--illustrating the art and science of software construction... -
![Computer Systems: A Programmers Perspective [with Introduction to RISC Assembly Language Programming] by Randal E. Bryant, David R. O'Hallaron]()
Computer Systems: A Programmers Perspective [with Introduction to RISC Assembly Language Programming] by Randal E. Bryant, David R. O'Hallaron
Rated: 4.40 of 5 stars · 10 ratingsFor Computer Organization and Architecture and Computer Systems courses in CS and EE and ECE departments. Developed out of an introductory course at Carnegie Mellon University, this text explains the important and enduring concepts underlying all computer systems, and shows the concrete ways that these ideas affect the correctness, performance, and utility of application programs... -
![Introduction to Algorithms by Thomas H. Cormen, Charles E Leiserson]()
Introduction to Algorithms by Thomas H. Cormen, Charles E Leiserson
Rated: 4.24 of 5 stars · 21 ratingsA comprehensive update of the leading algorithms text, with new material on matchings in bipartite graphs, online algorithms, machine learning, and other topics. Some books on algorithms are rigorous but incomplete; others cover masses of material but lack rigor. Introduction to Algorithms uniquely combines rigor and comprehensiveness... -
![Learn You a Haskell for Great Good! by Miran Lipovača]()
Learn You a Haskell for Great Good! by Miran Lipovača
Rated: 4.29 of 5 stars · 14 ratingsLearn You a Haskell for Great Good! is a fun, illustrated guide to learning Haskell, a functional programming language that's growing in popularity. Learn You a Haskell for Great Good! introduces programmers familiar with imperative languages (such as C++, Java, or Python) to the unique aspects of functional programming... -
![Pattern Recognition and Machine Learning by Christopher M. Bishop]()
Pattern Recognition and Machine Learning by Christopher M. Bishop
Rated: 4.29 of 5 stars · 14 ratingsPattern recognition has its origins in engineering, whereas machine learning grew out of computer science. However, these activities can be viewed as two facets of the same field, and together they have undergone substantial development over the past ten years...
![Computer Systems: A Programmers Perspective [with Introduction to RISC Assembly Language Programming] by Randal E. Bryant, David R. O'Hallaron](https://48f-1.s3.eu-west-2.amazonaws.com/books/small/6247f6501644e44564a69130.jpg)
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