Regular Expression Puzzles And Ai Coding Assistants
Download Regular Expression Puzzles And Ai Coding Assistants full books in PDF, epub, and Kindle. Read online free Regular Expression Puzzles And Ai Coding Assistants ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
| Author | : Mertz David |
| Publisher | : Simon and Schuster |
| Total Pages | : 150 |
| Release | : 2023-03-28 |
| Genre | : Computers |
| ISBN | : 1633437817 |
Learn how AI-assisted coding using ChatGPT and GitHub Copilot can dramatically increase your productivity (and fun) writing regular expressions and other programs. This book is the story of two competitors. On one side is David Mertz, an expert programmer and the author of the Web's most popular Regex tutorial. On the other are the AI powerhouse coding assistants, GitHub Copilot and OpenAI ChatGPT. Here's how the contest works: David invents 24 Regex problems he calls puzzles and shows you how to tackle each one. When he's done, he has Copilot and ChatGPT work the same puzzles. What they produce intrigues him. Which side is likelier to get it right? Which will write simple and elegant code? Which makes smarter use of lesser known Regex library features? Read the book to find out. David also offers AI best practices, showing how smart prompts return better results. By the end, you'll be a master at solving your own Regex puzzles, whether you use AI or not. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.
| Author | : Mertz David |
| Publisher | : Simon and Schuster |
| Total Pages | : 150 |
| Release | : 2023-04-11 |
| Genre | : Computers |
| ISBN | : 1638351880 |
Learn how AI-assisted coding using ChatGPT and GitHub Copilot can dramatically increase your productivity (and fun) writing regular expressions and other programs. Regular Expression Puzzles and AI Coding Assistants is the story of two competitors. On one side is David Mertz, an expert programmer and the author of the Web's most popular Regex tutorial. On the other are the AI powerhouse coding assistants, GitHub Copilot and OpenAI ChatGPT. Here's how the contest works: David invents 24 Regex problems he calls puzzles and shows you how to tackle each one. When he's done, he has Copilot and ChatGPT work the same puzzles. What they produce intrigues him. Which side is likelier to get it right? Which will write simple and elegant code? Which makes smarter use of lesser known Regex library features? Read the book to find out. David also offers AI best practices, showing how smart prompts return better results. By the end, you'll be a master at solving your own Regex puzzles, whether you use AI or not. About the technology Groundbreaking large language model research from OpenAI, Google, Amazon, and others have transformed expectations of machine-generated software. But how do these AI assistants, like ChatGPT and GitHub Copilot, measure up against regular expressions—a workhorse technology for developers used to describe, find, and manipulate patterns in text. Regular expressions are compact, complex, and subtle. Will AI assistants handle the challenge? About the book Regular Expression Puzzles and AI Coding Assistants is the perfect starting point for programmers of any experience level who want to understand the capabilities—and the limitations—of these exciting new tools. Author David Mertz presents 24 challenging regex puzzles, their traditional human-made solutions, and the fascinating answers given by popular AI assistants. Alongside these eye-opening puzzles you’ll learn how to write prompts, integrate AI-generated coding suggestions, and interact with the assistant to get the results you want. By the end of the book, you'll have a clear understanding of where AI assistants can reliably write code for you and where you’ll still need a human touch. Plus, you’ll learn a lot about regular expressions! About the reader Code examples use simple Python and Regular Expressions. No experience with AI coding tools required. About the author David Mertz is the founder of KDM Training and an acclaimed contributor to the Python community. He is also the author of The Puzzling Quirks of Regular Expressions, Cleaning Data for Effective Data Science: Doing the Other 80% of the Work, and other books. Table of Contents 1 The map and the territory 2 Quantifiers and special sub-patterns 3 Pitfalls and sand in the gears 4 Creating functions using regex 5 Easy, difficult, and impossible tasks 6 Conclusions Appendix A: Learning to use regular expressions
| Author | : David Mertz |
| Publisher | : Addison-Wesley Professional |
| Total Pages | : 669 |
| Release | : 2023-11-02 |
| Genre | : Computers |
| ISBN | : 0138320934 |
Move Beyond Python Code That "Mostly Works" to Code That Is Expressive, Robust, and Efficient Python is arguably the most-used programming language in the world, with applications from primary school education to workaday web development, to the most advanced scientific research institutes. While there are many ways to perform a task in Python, some are wrong, inelegant, or inefficient. Better Python Code is a guide to "Pythonic" programming, a collection of best practices, ways of working, and nuances that are easy to miss, especially when ingrained habits are borrowed from other programming languages. Author David Mertz presents concrete and concise examples of various misunderstandings, pitfalls, and bad habits in action. He explains why some practices are better than others, based on his 25+ years of experience as an acclaimed contributor to the Python community. Each chapter thoroughly covers related clusters of concepts, with chapters sequenced in ascending order of sophistication. Whether you are starting out with Python or are an experienced developer pushing through the limitations of your Python code, this book is for all who aspire to be more Pythonic when writing better Python code. Use the right kind of loops in Python Learn the ins and outs of mutable and immutable objects Get expert advice to avoid Python "gotchas" Examine advanced Python topics Navigate the "attractive nuisances" that exist in Python Learn the most useful data structures in Python and how to avoid misusing them Avoid security mistakes Understand the basics of numeric computation, including floating point numbers and numeric datatypes "My high expectations for this engaging Python book have been exceeded: it offers a great deal of insight for intermediate or advanced programmers to improve their Python skills, includes copious sharing of precious experience practicing and teaching the language, yet remains concise, easy to read, and conversational." --From the Foreword by Alex Martelli Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.
| Author | : David Mertz |
| Publisher | : Packt Publishing Ltd |
| Total Pages | : 499 |
| Release | : 2021-03-31 |
| Genre | : Mathematics |
| ISBN | : 1801074402 |
Think about your data intelligently and ask the right questions Key FeaturesMaster data cleaning techniques necessary to perform real-world data science and machine learning tasksSpot common problems with dirty data and develop flexible solutions from first principlesTest and refine your newly acquired skills through detailed exercises at the end of each chapterBook Description Data cleaning is the all-important first step to successful data science, data analysis, and machine learning. If you work with any kind of data, this book is your go-to resource, arming you with the insights and heuristics experienced data scientists had to learn the hard way. In a light-hearted and engaging exploration of different tools, techniques, and datasets real and fictitious, Python veteran David Mertz teaches you the ins and outs of data preparation and the essential questions you should be asking of every piece of data you work with. Using a mixture of Python, R, and common command-line tools, Cleaning Data for Effective Data Science follows the data cleaning pipeline from start to end, focusing on helping you understand the principles underlying each step of the process. You'll look at data ingestion of a vast range of tabular, hierarchical, and other data formats, impute missing values, detect unreliable data and statistical anomalies, and generate synthetic features. The long-form exercises at the end of each chapter let you get hands-on with the skills you've acquired along the way, also providing a valuable resource for academic courses. What you will learnIngest and work with common data formats like JSON, CSV, SQL and NoSQL databases, PDF, and binary serialized data structuresUnderstand how and why we use tools such as pandas, SciPy, scikit-learn, Tidyverse, and BashApply useful rules and heuristics for assessing data quality and detecting bias, like Benford’s law and the 68-95-99.7 ruleIdentify and handle unreliable data and outliers, examining z-score and other statistical propertiesImpute sensible values into missing data and use sampling to fix imbalancesUse dimensionality reduction, quantization, one-hot encoding, and other feature engineering techniques to draw out patterns in your dataWork carefully with time series data, performing de-trending and interpolationWho this book is for This book is designed to benefit software developers, data scientists, aspiring data scientists, teachers, and students who work with data. If you want to improve your rigor in data hygiene or are looking for a refresher, this book is for you. Basic familiarity with statistics, general concepts in machine learning, knowledge of a programming language (Python or R), and some exposure to data science are helpful.
| Author | : David Mertz |
| Publisher | : Addison-Wesley Professional |
| Total Pages | : 544 |
| Release | : 2003 |
| Genre | : Computers |
| ISBN | : 9780321112545 |
bull; Demonstrates how Python is the perfect language for text-processing functions. bull; Provides practical pointers and tips that emphasize efficient, flexible, and maintainable approaches to text-processing challenges. bull; Helps programmers develop solutions for dealing with the increasing amounts of data with which we are all inundated.
| Author | : David Mertz |
| Publisher | : |
| Total Pages | : 48 |
| Release | : 2018-02-23 |
| Genre | : |
| ISBN | : 9781985826748 |
In this document, we'll take a tour of Python's features suitable for implementing programs in a functional style. After an introduction to the concepts of functional programming, we'll look at language features such as iterators and generators and relevant library modules such as itertools and functools.
| Author | : Roberto Pieraccini |
| Publisher | : MIT Press |
| Total Pages | : 290 |
| Release | : 2021-09-07 |
| Genre | : Computers |
| ISBN | : 0262542552 |
An accessible explanation of the technologies that enable such popular voice-interactive applications as Alexa, Siri, and Google Assistant. Have you talked to a machine lately? Asked Alexa to play a song, asked Siri to call a friend, asked Google Assistant to make a shopping list? This volume in the MIT Press Essential Knowledge series offers a nontechnical and accessible explanation of the technologies that enable these popular devices. Roberto Pieraccini, drawing on more than thirty years of experience at companies including Bell Labs, IBM, and Google, describes the developments in such fields as artificial intelligence, machine learning, speech recognition, and natural language understanding that allow us to outsource tasks to our ubiquitous virtual assistants. Pieraccini describes the software components that enable spoken communication between humans and computers, and explains why it's so difficult to build machines that understand humans. He explains speech recognition technology; problems in extracting meaning from utterances in order to execute a request; language and speech generation; the dialog manager module; and interactions with social assistants and robots. Finally, he considers the next big challenge in the development of virtual assistants: building in more intelligence--enabling them to do more than communicate in natural language and endowing them with the capacity to know us better, predict our needs more accurately, and perform complex tasks with ease.
| Author | : Anany Levitin |
| Publisher | : OUP USA |
| Total Pages | : 280 |
| Release | : 2011-10-14 |
| Genre | : Computers |
| ISBN | : 0199740445 |
Algorithmic puzzles are puzzles involving well-defined procedures for solving problems. This book will provide an enjoyable and accessible introduction to algorithmic puzzles that will develop the reader's algorithmic thinking. The first part of this book is a tutorial on algorithm design strategies and analysis techniques. Algorithm design strategies — exhaustive search, backtracking, divide-and-conquer and a few others — are general approaches to designing step-by-step instructions for solving problems. Analysis techniques are methods for investigating such procedures to answer questions about the ultimate result of the procedure or how many steps are executed before the procedure stops. The discussion is an elementary level, with puzzle examples, and requires neither programming nor mathematics beyond a secondary school level. Thus, the tutorial provides a gentle and entertaining introduction to main ideas in high-level algorithmic problem solving. The second and main part of the book contains 150 puzzles, from centuries-old classics to newcomers often asked during job interviews at computing, engineering, and financial companies. The puzzles are divided into three groups by their difficulty levels. The first fifty puzzles in the Easier Puzzles section require only middle school mathematics. The sixty puzzle of average difficulty and forty harder puzzles require just high school mathematics plus a few topics such as binary numbers and simple recurrences, which are reviewed in the tutorial. All the puzzles are provided with hints, detailed solutions, and brief comments. The comments deal with the puzzle origins and design or analysis techniques used in the solution. The book should be of interest to puzzle lovers, students and teachers of algorithm courses, and persons expecting to be given puzzles during job interviews.
| Author | : Jan Goyvaerts |
| Publisher | : "O'Reilly Media, Inc." |
| Total Pages | : 612 |
| Release | : 2012-08-13 |
| Genre | : Computers |
| ISBN | : 1449327486 |
Take the guesswork out of using regular expressions. With more than 140 practical recipes, this cookbook provides everything you need to solve a wide range of real-world problems. Novices will learn basic skills and tools, and programmers and experienced users will find a wealth of detail. Each recipe provides samples you can use right away. This revised edition covers the regular expression flavors used by C#, Java, JavaScript, Perl, PHP, Python, Ruby, and VB.NET. You’ll learn powerful new tricks, avoid flavor-specific gotchas, and save valuable time with this huge library of practical solutions. Learn regular expressions basics through a detailed tutorial Use code listings to implement regular expressions with your language of choice Understand how regular expressions differ from language to language Handle common user input with recipes for validation and formatting Find and manipulate words, special characters, and lines of text Detect integers, floating-point numbers, and other numerical formats Parse source code and process log files Use regular expressions in URLs, paths, and IP addresses Manipulate HTML, XML, and data exchange formats Discover little-known regular expression tricks and techniques
| Author | : Peter Van der Linden |
| Publisher | : Prentice Hall Professional |
| Total Pages | : 379 |
| Release | : 1994 |
| Genre | : Computers |
| ISBN | : 0131774298 |
Software -- Programming Languages.
