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Get Coding with Data

Author : Kevin Wood

Publisher : The Rosen Publishing Group, Inc

Page : 34 pages

File Size : 16,75 MB

Release : 2017-07-15

Category : Juvenile Nonfiction

ISBN : 1499482531

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Book Description

Code it, test it, cache it, drop it! This comprehensive book introduces readers to everything they need to know about data. Accessible language provides easy-to-understand explanations for crucial concepts. Puzzles, games, and robot illustrations create a fun, interactive learning experience that will draw in both beginning coders and readers who are reluctant to learn about coding. They�ll explore types of data including numbers, strings, and arrays. Readers will learn how data is stored in computer and in codes, as well as key vocabulary terms such as memory, cache, ram, disk, and flash. They�ll also see the difference between constants and variables, and other important science and technology topics, all while having fun!



Get Coding with Data

Author : Kevin Wood

Publisher : The Rosen Publishing Group, Inc

Page : 35 pages

File Size : 50,8 MB

Release : 2017-07-15

Category : Juvenile Nonfiction

ISBN : 1499482493

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Book Description

Code it, test it, cache it, drop it! This comprehensive book introduces readers to everything they need to know about data. Accessible language provides easy-to-understand explanations for crucial concepts. Puzzles, games, and robot illustrations create a fun, interactive learning experience that will draw in both beginning coders and readers who are reluctant to learn about coding. They�ll explore types of data including numbers, strings, and arrays. Readers will learn how data is stored in computer and in codes, as well as key vocabulary terms such as memory, cache, ram, disk, and flash. They�ll also see the difference between constants and variables, and other important science and technology topics, all while having fun!



R for Data Science

Author : Hadley Wickham

Publisher : "O'Reilly Media, Inc."

Page : 521 pages

File Size : 42,82 MB

Release : 2016-12-12

Category : Computers

ISBN : 1491910364

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Book Description

Learn 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. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way. You'll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results



Learn Data Analysis with Python

Author : A.J. Henley

Publisher : Apress

Page : 103 pages

File Size : 13,54 MB

Release : 2018-02-22

Category : Computers

ISBN : 1484234863

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Book Description

Get started using Python in data analysis with this compact practical guide. This book includes three exercises and a case study on getting data in and out of Python code in the right format. Learn Data Analysis with Python also helps you discover meaning in the data using analysis and shows you how to visualize it. Each lesson is, as much as possible, self-contained to allow you to dip in and out of the examples as your needs dictate. If you are already using Python for data analysis, you will find a number of things that you wish you knew how to do in Python. You can then take these techniques and apply them directly to your own projects. If you aren’t using Python for data analysis, this book takes you through the basics at the beginning to give you a solid foundation in the topic. As you work your way through the book you will have a better of idea of how to use Python for data analysis when you are finished. What You Will Learn Get data into and out of Python code Prepare the data and its format Find the meaning of the data Visualize the data using iPython Who This Book Is For Those who want to learn data analysis using Python. Some experience with Python is recommended but not required, as is some prior experience with data analysis or data science.



Programming Skills For Data Science

Author : Freeman

Publisher : Pearson Education India

Page : 397 pages

File Size : 14,24 MB

Release :

Category :

ISBN : 9353942632

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Book Description

Programming Skills for Data Science brings together all the foundation skills needed to transform raw data into actionable insights for domains ranging from urban planning to precision medicine, even if you have no programming or data science experience. Guided by expert instructors Michael Freeman and Joel Ross, this book will help learners install the tools required to solve professional-level data science problems, including widely used R language, RStudio integrated development environment, and Git version-control system. It explains how to wrangle data into a form where it can be easily used, analyzed, and visualized so others can see the patterns uncovered. Step by step, students will master powerful R programming techniques and troubleshooting skills for probing data in new ways, and at larger scales.



Data-Oriented Programming

Author : Yehonathan Sharvit

Publisher : Simon and Schuster

Page : 422 pages

File Size : 46,89 MB

Release : 2022-08-16

Category : Computers

ISBN : 1617298573

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Book Description

Eliminate the unavoidable complexity of object-oriented designs. The innovative data-oriented programming paradigm makes your systems less complex by making it simpler to access and manipulate data. In Data-Oriented Programming you will learn how to: Separate code from data Represent data with generic data structures Manipulate data with general-purpose functions Manage state without mutating data Control concurrency in highly scalable systems Write data-oriented unit tests Specify the shape of your data Benefit from polymorphism without objects Debug programs without a debugger Data-Oriented Programming is a one-of-a-kind guide that introduces the data-oriented paradigm. This groundbreaking approach represents data with generic immutable data structures. It simplifies state management, eases concurrency, and does away with the common problems you’ll find in object-oriented code. The book presents powerful new ideas through conversations, code snippets, and diagrams that help you quickly grok what’s great about DOP. Best of all, the paradigm is language-agnostic—you’ll learn to write DOP code that can be implemented in JavaScript, Ruby, Python, Clojure, and also in traditional OO languages like Java or C#. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Code that combines behavior and data, as is common in object-oriented designs, can introduce almost unmanageable complexity for state management. The Data-oriented programming (DOP) paradigm simplifies state management by holding application data in immutable generic data structures and then performing calculations using non-mutating general-purpose functions. Your applications are free of state-related bugs and your code is easier to understand and maintain. About the book Data-Oriented Programming teaches you to design software using the groundbreaking data-oriented paradigm. You’ll put DOP into action to design data models for business entities and implement a library management system that manages state without data mutation. The numerous diagrams, intuitive mind maps, and a unique conversational approach all help you get your head around these exciting new ideas. Every chapter has a lightbulb moment that will change the way you think about programming. What's inside Separate code from data Represent data with generic data structures Manage state without mutating data Control concurrency in highly scalable systems Write data-oriented unit tests Specify the shape of your data About the reader For programmers who have experience with a high-level programming language like JavaScript, Java, Python, C#, Clojure, or Ruby. About the author Yehonathan Sharvit has over twenty years of experience as a software engineer. He blogs, speaks at conferences, and leads Data-Oriented Programming workshops around the world. Table of Contents PART 1 FLEXIBILITY 1 Complexity of object-oriented programming 2 Separation between code and data 3 Basic data manipulation 4 State management 5 Basic concurrency control 6 Unit tests PART 2 SCALABILITY 7 Basic data validation 8 Advanced concurrency control 9 Persistent data structures 10 Database operations 11 Web services PART 3 MAINTAINABILITY 12 Advanced data validation 13 Polymorphism 14 Advanced data manipulation 15 Debugging



R Programming for Data Science

Author : Roger D. Peng

Publisher :

Page : 0 pages

File Size : 19,42 MB

Release : 2012-04-19

Category : R (Computer program language)

ISBN : 9781365056826

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Book Description

Data science has taken the world by storm. Every field of study and area of business has been affected as people increasingly realize the value of the incredible quantities of data being generated. But to extract value from those data, one needs to be trained in the proper data science skills. The R programming language has become the de facto programming language for data science. Its flexibility, power, sophistication, and expressiveness have made it an invaluable tool for data scientists around the world. This book is about the fundamentals of R programming. You will get started with the basics of the language, learn how to manipulate datasets, how to write functions, and how to debug and optimize code. With the fundamentals provided in this book, you will have a solid foundation on which to build your data science toolbox.



Coding for Data and Computer Communications

Author : David Salomon

Publisher : Springer Science & Business Media

Page : 550 pages

File Size : 11,45 MB

Release : 2006-02-28

Category : Computers

ISBN : 0387238042

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Book Description

Details the most important techniques used to make the storage and transmission of data fast, secure, and reliable. Accessible to both specialists and nonspecialists: Avoids complex mathematics



Python Data Science Handbook

Author : Jake VanderPlas

Publisher : "O'Reilly Media, Inc."

Page : 609 pages

File Size : 12,33 MB

Release : 2016-11-21

Category : Computers

ISBN : 1491912138

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Book Description

For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools. Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python. With this handbook, you’ll learn how to use: IPython and Jupyter: provide computational environments for data scientists using Python NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python Matplotlib: includes capabilities for a flexible range of data visualizations in Python Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms



Python Machine Learning for Beginners

Author : Leonard Deep

Publisher :

Page : 236 pages

File Size : 10,19 MB

Release : 2019-05-13

Category :

ISBN : 9781097858309

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Book Description

Are you interested to get into the programming world? Do you want to learn and understand Python and Machine Learning? Python Machine Learning for Beginners is the guide for you. Python Machine Learning for Beginners is the ultimate guide for beginners looking to learn and understand how Python programming works. Python Machine Learning for Beginners is split up into easy to learn chapters that will help guide the readers through the early stages of Python programming. It's this thought out and systematic approach to learning which makes Python Machine Learning for Beginners such a sought-after resource for those that want to learn about Python programming and about Machine Learning using an object-oriented programming approach. Inside Python Machine Learning for Beginners you will discover: An introduction to Machine Learning The main concepts of Machine Learning The basics of Python for beginners Machine Learning with Python Data Processing, Analysis, and Visualizations Case studies and much more! Throughout the book, you will learn the basic concepts behind Python programming which is designed to introduce you to Python programming. You will learn about getting started, the keywords and statements, data types and type conversion. Along with different examples, there are also exercises to help ensure that the information sinks in. You will find this book an invaluable tool for starting and mastering Machine Learning using Python. Once you complete Python Machine Learning for Beginners, you will be more than prepared to take on any Python programming. Scroll back up to the top of this page and hit BUY IT NOW to get your copy of Python Machine Learning for Beginners! You won't regret it!