Search results for [Visual programming languages (Computer science)] at NC Cardinal

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Python for data science / by Mueller, John,1958-author.(CARDINAL)203899; Massaron, Luca,author.(CARDINAL)349112;

Part 1: Getting started with data science and Python -- Part 2: Getting your hands dirty with data -- Part 3: Visualizing information -- Part 4: Wrangling data -- Part 5: Learning from data -- Part 6: The part of tens.Python is a general-purpose programming language created in the late 1980s--and named after Monty Python--that's used by thousands of people to do things from testing microchips at Intel, to powering Instagram, to building video games with the PyGame library.

Subjects: Python (Computer program language); Data mining.; Quantitative research; Quantitative research;

Available copies: 1 / Total copies: 2

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Mastering Visual studio code : a beginner's guide / by Bin Uzayr, Sufyan,editor.(CARDINAL)872443;

Includes bibliographical references and index.Introduction to VS code -- Exploring the user interface -- Files & folders & project -- Editing code in your language -- Integrating with source control -- Debugging code -- VS code extensions -- Appraisal."This book is a detailed guide that will help learners get started with VS Code programming. It talks about the basics and then moves on to practical exercises to help readers quickly gain the required knowledge. This book is meant for both developers as well as learners without a formal background"--

Subjects: Microsoft Visual studio.; Web site development; Application software;

Available copies: 1 / Total copies: 1

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Code this game! / by Ray, Meg(Computer science teacher),author.(CARDINAL)816673; Zoo, Keith,artist.(CARDINAL)675766;

part 1. Introduction -- part 2. Code this game. Set up the game window ; Adding assets ; Drawing shapes ; Background grid ; Make your own classes ; Adding enemies ; Moving the pizzas ; Interactive fields ; Collision detection ; Adding points over time ; Applying traps ; Connecting traps to the grid ; Win and lose conditions -- part 3. Break this game. Customize your game ; Mod your game ; Hack your game ; Explore new games -- Appendix. Share your game -- Appendix. Keep coding -- Appendix. Common bugs -- Gallery of downloadable assets.Presented in an easelback format that allows kids to read and program simultaneously, this visual guide includes step-by-step instructions for using the open-source Python programming language to create a personalized strategy action video game called "Attack of the vampire pizzas!"

Subjects: Instructional and educational works.; Handbooks and manuals.; Illustrated works.; Python (Computer program language); Video games; Scripting languages (Computer science);

Available copies: 1 / Total copies: 5

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Python / by Hart-Davis, Guy,author.(CARDINAL)352260; Hart-Davis, Ted,author.(CARDINAL)857705;

Teach Yourself VISUALLY: Python is your personal guide to getting you started in programming. As one of the world's most popular-and most accessible-coding languages, Python is your gateway into the wide and wonderful world of computer science. This hands-on guide walks you through Python step by clearly illustrated step, from writing your very first Python code in a terminal window or the VS Code app through to creating your own lists, dictionaries, and custom classes.

Subjects: Educational and instructional works.; Computer programming.; Python (Computer program language);

Available copies: 3 / Total copies: 5

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Teach yourself visually python / by Hart-Davis, Guy,Author(DLC)n 94026772 ; Hart-Davis, Ted,Author(DLC)no2022114225;

A simple, straightforward, and hands-on roadmap to the world of computer programming with Python Teach Yourself VISUALLY: Python is your personal guide to getting you started in programming. As one of the world's most popular and most accessible coding languages, Python is your gateway into the wide and wonderful world of computer science. This hands-on guide walks you through Python step by clearly illustrated step, from writing your very first Python code in a terminal window or the VS Code app through to creating your own lists, dictionaries, and custom classes. In the book, you'll learn to: *Install Python and the tools you need to work with it on Windows, macOS, and Linux *Work with files and folders, manipulate text, and create powerful functions that do exactly what you want *Write clean code that makes decisions effectively, repeats actions as needed, and handles any errors that occur A must-have resource for aspiring programmers starting from the very beginning, Teach Yourself VISUALLY: Python is also an indispensable handbook for programmers making a transition from another language.

Subjects: Python (Computer program language); Computer programming.; Object-oriented programming (Computer science);

Available copies: 1 / Total copies: 1

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Learn enough Python to be dangerous : software development, flask web apps, and beginning data science with Python / by Hartl, Michael,author.;

Includes bibliographical references (pages 403-404) and index."Python is the dominant programming language for data science and an ideal first programming language for web development and many other uses. In Learn Enough Python to Be Dangerous, renowned instructor Michael Hartl teaches the specific concepts, skills, and approaches you need to be professionally productive. Even if you've never programmed before, Hartl helps you quickly build technical sophistication and master the lore you need to succeed. Hartl introduces Python both as a general-purpose language and as a specialist tool for web development and data science, presenting focused examples and exercises that help you internalize what matters, without wasting time on details pros don't care about. Learn enough about applying core Python concepts with the interactive interpreter and command line; writing object-oriented code with Python's native objects; developing and publishing self-contained Python packages; using elegant, powerful functional programming techniques; building new objects, and extending them via Test-Driven Development (TDD); leveraging Python's exceptional shell scripting capabilities; creating and deploying a full web app, using routes, layouts, embedded Python, and forms; getting started with data science tools for calculation, visualization, analysis, and machine learning; and mastering concrete and informal skills every developer needs"--

Subjects: Python (Computer program language); Computer programming.;

Available copies: 2 / Total copies: 2

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Head first Ruby / by McGavren, Jay,author.(CARDINAL)623907;

Includes bibliographical references (page 513) and index."What will you learn from this book? What's all the buzz about this Ruby language? Is it right for you? Well, ask yourself: are you tired of all those extra declarations, keywords, and compilation steps in your other languages? Do you want to be a more productive programmer? Then you'll love Ruby. WIth this unique hands-on learning experience, you'll discover how Ruby takes care of all the details for you, so you can simply have fun and get more done with less code. What's so special about this book? Based on the latest research in cognitive science and learning theory, Head First Ruby uses a visually rich format to engage your mind, rather than a text-heavy approach that puts you to sleep. Why waste your time struggling with new concepts? This multi-sensory learning experience is designed for the way your brain really works."--More with less : code the way you want -- Methods and classes : getting organized -- Inheritance : relying on your parents -- Initializing instances : off to a great start -- Arrays and blocks : better than loops -- Block return values : how should I handle this? -- Hashes : labeling data -- References : crossed signals -- Mixins : mix it up -- Comparable and enumerable : ready-made mixes -- Documentation : read the manual -- Exceptions : handling the unexpected -- Unit testing : code quality assurance -- Web apps : serving HTML -- Saving and loading data : keep it around -- Leftovers : the top ten topics (we didn't cover).

Subjects: Ruby (Computer program language); Object-oriented programming (Computer science);

Available copies: 3 / Total copies: 3

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Text mining with R : a tidy approach / by Silge, Julia,author.; Robinson, David,author.;

Includes bibliographical references (pages 173-174) and index.Much of the data available today is unstructured and text-heavy, making it challenging for analysts to apply their usual data wrangling and visualization tools. With this practical book, you'll explore text-mining techniques with tidytext, a package that authors Julia Silge and David Robinson developed using the tidy principles behind R packages like ggraph and dplyr . You'll learn how tidytext and other tidy tools in R can make text analysis easier and more effective. The authors demonstrate how treating text as data frames enables you to manipulate, summarize, and visualize characteristics of text. You'll also learn how to integrate natural language processing (NLP) into effective workflows. Practical code examples and data explorations will help you generate real insights from literature, news, and social media. Learn how to apply the tidy text format to NLP Use sentiment analysis to mine the emotional content of text Identify a document's most important terms with frequency measurements Explore relationships and connections between words with the ggraph and widyr packages Convert back and forth between R's tidy and non-tidy text formats Use topic modeling to classify document collections into natural groups Examine case studies that compare Twitter archives, dig into NASA metadata, and analyze thousands of Usenet messages

Subjects: Data mining.; Text processing (Computer science); R (Computer program language);

Available copies: 0 / Total copies: 1

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College majors handbook : with real career paths and payoffs : the actual jobs, earnings, and trends for graduates of 50 college majors / by Fogg, Neeta.(CARDINAL)635302;

What you need to know about the college investment decision, college success, and career choice. What pays off in high school : pre-college decisions and college and career choices ; The psychology of career choice : assessing abilities, interests, and values ; The economics of career choice -- Behavioral and medical sciences. Family and consumer sciences ; Health and medical technology ; Medical preparatory programs ; Nursing ; Parks, recreation, fitness, and leisure studies ; Pharmacy ; Physical therapy ; Psychology -- Business and administration. Accounting ; Applied mathematics, operations research, and statistics; Economics ; Financial management ; General business ; General mathematics ; Marketing ; Public administration -- Education. Elementary teacher education ; Mathematics and science teacher education ; Physical education and coaching ; Preschool/kindergarten/ early childhood teacher education ; Secondary teacher education ; Special education -- Engineering. Aerospace, aeronautical, and astronautical engineering ; Architecture and environmental design ; Chemical engineering ; Civil engineering ; Computer systems engineering ; Electrical and electronics engineering ; Industrial engineering ; Mechanical engineering -- Humanities and social sciences. Anthropology and archaeology ; Communications ; Dramatic arts ; English language, literature and letters ; Foreign languages and literature ; Geography ; History ; Journalism ; Legal studies and pre-law ; Liberal arts and general studies ; Music and dance ; Philosophy and religion ; Political science, government, and international relations; Sociology ; Visual arts -- Natural sciences. Animal science ; Biology and life sciences ; Chemistry ; Forestry and environmental science ; Geology and geophysics ; Microbiology and biochemistry ; Physics and astronomy ; Plant science -- Technology. Computer science ; Electrical and electronics engineering technology ; Industrial production technology ; Information systems ; Mechanical engineering technology.

Subjects: Career education; College majors; Professions; Universities and colleges; Vocational guidance; Vocational interests;

Available copies: 4 / Total copies: 4

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Learn data mining through excel : a step-by-step approach for understanding machine learning methods / by Zhou, Hong,author.;

Use popular data mining techniques in Microsoft Excel to better understand machine learning methods. Software tools and programming language packages take data input and deliver data mining results directly, presenting no insight on working mechanics and creating a chasm between input and output. This is where Excel can help. Excel allows you to work with data in a transparent manner. When you open an Excel file, data is visible immediately and you can work with it directly. Intermediate results can be examined while you are conducting your mining task, offering a deeper understanding of how data is manipulated and results are obtained. These are critical aspects of the model construction process that are hidden in software tools and programming language packages. This book teaches you data mining through Excel. You will learn how Excel has an advantage in data mining when the data sets are not too large. It can give you a visual representation of data mining, building confidence in your results. You will go through every step manually, which offers not only an active learning experience, but teaches you how the mining process works and how to find the internal hidden patterns inside the data. What You Will Learn *Comprehend data mining using a visual step-by-step approach *Build on a theoretical introduction of a data mining method, followed by an Excel implementation *Unveil the mystery behind machine learning algorithms, making a complex topic accessible to everyone *Become skilled in creative uses of Excel formulas and functions *Obtain hands-on experience with data mining and Excel. Who This Book Is For Anyone who is interested in learning data mining or machine learning, especially data science visual learners and people skilled in Excel, who would like to explore data science topics and/or expand their Excel skills. A basic or beginner level understanding of Excel is recommended.

Subjects: Microsoft Excel (Computer file); Data mining.; Machine learning.;

Available copies: 1 / Total copies: 1

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