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Regular Expression Puzzles And Ai Coding Assistants


Regular Expression Puzzles And Ai Coding Assistants
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Regular Expression Puzzles And Ai Coding Assistants


Regular Expression Puzzles And Ai Coding Assistants
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Author : David Mertz
language : en
Publisher: Simon and Schuster
Release Date : 2023-04-04

Regular Expression Puzzles And Ai Coding Assistants written by David Mertz and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-04 with Computers categories.


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 will 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 will have a clear understanding of where AI assistants can reliably write code for you and where you will still need a human touch. Plus, you will learn a lot about regular expressions! About the reader Code examples use simple Python and Regular Expressions. No experience with AI coding tools is required.



Regular Expression Puzzles And Ai Coding Assistants


Regular Expression Puzzles And Ai Coding Assistants
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Author : David Mertz
language : en
Publisher: Simon and Schuster
Release Date : 2023-04-11

Regular Expression Puzzles And Ai Coding Assistants written by David Mertz and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-11 with Computers categories.


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



Build Financial Software With Generative Ai From Scratch


Build Financial Software With Generative Ai From Scratch
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Author : Christopher Kardell
language : en
Publisher: Simon and Schuster
Release Date : 2025-05-20

Build Financial Software With Generative Ai From Scratch written by Christopher Kardell and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-20 with Computers categories.


Build working and regulation-compliant financial software—from scratch! The software used by banks, trading firms, and other financial services has special requirements at every level, from securing the UI to making sure backend services comply with a host of regulations. Build Financial Software with Generative AI (From Scratch) shows you how to deliver full stack financial services software—and how generative AI can make you even more productive. In Build Financial Software with Generative AI (From Scratch) you will: • Explore the core concepts of FinTech • Speed development with generative AI tools • Develop and deploy containerized services • Create and document APIs • Effectively visualize your data In Build Financial Software with Generative AI (From Scratch) you’ll build working software for processing Automated Clearing House (ACH) files, a cornerstone technology of banking that moves trillions of dollars every year. You’ll work with generative AI technology throughout the full stack application, including researching the tech for your application, spinning up a bare bone starting project, answering domain questions, clarifying functionality, and troubleshooting. Along the way, you’ll learn what sets FinTech projects apart from normal web apps. About the technology The financial industry is awash with regulatory and compliance challenges, complex technical requirements, and stringent security demands. There’s a huge demand for developers who can create financial services software and this book will get you started. You’ll build your own FinTech app from the ground up—with a big productivity boost from Generative AI! About the book Build Financial Software with Generative AI (From Scratch) guides you through modernizing a full-stack Automated Clearing House (ACH) application, layer-by-layer. You’ll start with a quick review of FinTech basics and an introduction to GenAI tools. Then, you’ll develop a data visualization dashboard with React, containerize components with Docker, create and refine APIs, implement backend processing, and even design a custom database. Throughout, you’ll see how AI tools aid with coding, testing, research, security, documentation, and even Agile practices. What's inside • Learn the core concepts of FinTech development • Create and document APIs using Generative AI • Build an awesome data visualization dashboard About the reader Examples are in Python. No experience with generative AI or financial services required. About the author Christopher Kardell and Mark Brouwer have both spent more than 20 years working in the Fintech industry. Table of Contents Part 1 1 Exploring FinTech and generative AI 2 Parsing payments Part 2 3 Getting started with Docker 4 APIs: The piping between our components 5 Storing our ACH files 6 Taking the next step with Next.js 7 Our minimum viable product Part 3 8 Exceptions 9 Searching and auditing 10 Company information 11 International ACH transactions and OFAC scanning 12 Where to go from here



Better Python Code


Better Python Code
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Author : David Mertz
language : en
Publisher: Addison-Wesley Professional
Release Date : 2023-11-02

Better Python Code written by David Mertz and has been published by Addison-Wesley Professional this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-02 with Computers categories.


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.



Regular Expressions Cookbook


Regular Expressions Cookbook
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Author : Jan Goyvaerts
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2012-08-13

Regular Expressions Cookbook written by Jan Goyvaerts and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-08-13 with Computers categories.


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



Cleaning Data For Effective Data Science


Cleaning Data For Effective Data Science
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Author : David Mertz
language : en
Publisher: Packt Publishing Ltd
Release Date : 2021-03-31

Cleaning Data For Effective Data Science written by David Mertz and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-31 with Mathematics categories.


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.



Text Processing In Python


Text Processing In Python
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Author : David Mertz
language : en
Publisher: Addison-Wesley Professional
Release Date : 2003

Text Processing In Python written by David Mertz and has been published by Addison-Wesley Professional this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with Computers categories.


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.



Artificial Intelligence And Games


Artificial Intelligence And Games
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Author : Georgios N. Yannakakis
language : en
Publisher: Springer
Release Date : 2018-02-17

Artificial Intelligence And Games written by Georgios N. Yannakakis and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-02-17 with Computers categories.


This is the first textbook dedicated to explaining how artificial intelligence (AI) techniques can be used in and for games. After introductory chapters that explain the background and key techniques in AI and games, the authors explain how to use AI to play games, to generate content for games and to model players. The book will be suitable for undergraduate and graduate courses in games, artificial intelligence, design, human-computer interaction, and computational intelligence, and also for self-study by industrial game developers and practitioners. The authors have developed a website (http://www.gameaibook.org) that complements the material covered in the book with up-to-date exercises, lecture slides and reading.



Programming Game Ai By Example


Programming Game Ai By Example
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Author : Mat Buckland
language : en
Publisher: Jones & Bartlett Learning
Release Date : 2005

Programming Game Ai By Example written by Mat Buckland and has been published by Jones & Bartlett Learning this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with Computers categories.


This book describes in detail many of the AI techniques used in modern computer games, explicity shows how to implement these practical techniques within the framework of several game developers with a practical foundation to game AI.



Expert C Programming


Expert C Programming
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Author : Peter Van der Linden
language : en
Publisher: Prentice Hall Professional
Release Date : 1994

Expert C Programming written by Peter Van der Linden and has been published by Prentice Hall Professional this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994 with Computers categories.


Software -- Programming Languages.