By Warren Sande, Carter Sande
A light yet thorough advent to the realm of desktop programming, it's written in language a 12-year-old can stick to, yet somebody who desires to the right way to software a working laptop or computer can use it. Even adults. Written via Warren Sande and his son, Carter, and reviewed via expert educators, this e-book is kid-tested and parent-approved.
About This Book
Learn to speak on your machine in its personal language! no matter if you need to create a video game, begin a enterprise, or clear up a huge challenge, step one is studying to jot down your personal courses. Programming is a enjoyable problem, and it's effortless to get started!
This up-to-date and revised version of hi international! introduces the area of machine programming in a transparent and fascinating type. Written via Warren Sande and his son, Carter, it's jam-packed with examples that would get you considering and studying. Reviewed through specialist educators, this e-book is kid-tested and parent-approved. You don't want to know whatever approximately programming to exploit the publication, simply the fundamentals of utilizing a working laptop or computer. if you happen to can commence a software and shop a dossier, you'll be off and running!
Purchase of the print e-book features a loose booklet in PDF, Kindle, and ePub codecs from Manning Publications.
• Explains recommendations in transparent language
• plenty of images, cartoons, and enjoyable examples
• whole set of perform questions and exercises
• Illustrated in complete color
• Hello World! makes use of Python, a programming language designed to be effortless to profit. utilizing enjoyable examples, it brings to existence strategies of computing— looping, judgements, enter and output, information constructions, graphics—and many more.
About the Authors
Warren Sande is an digital platforms engineer who makes use of Python either as a "do anything" scripting language and so that it will train pcs and programming. Carter Sande is a highschool pupil who's keen about expertise. while he's now not solving his school's community and assisting his classmates get better misplaced homework, he loves to trip his motorcycle and write unfashionable video games.
Table of Contents
1. Getting Started
2. bear in mind This: reminiscence and Variables
3. easy Math
4. forms of Data
6. GUIs—Graphical person Interfaces
7. judgements, Decisions
8. Loop the Loop
9. only for You—Comments
10. online game Time
11. Nested and Variable Loops
12. accumulating issues Together—Lists and Dictionaries
17. Sprites and Collision Detection
18. a brand new type of Input—Events
20. extra GUIs
21. Print Formatting and Strings
22. dossier enter and Output
23. Take a Chance—Randomness
24. desktop Simulations
25. Skier Explained
26. Python Battle
27. What's subsequent?
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Extra info for Hello World!: Computer Programming for Kids and Other Beginners (2nd Edition)
I wanted the reader to feel the power of the NLTK library, and build a small running example that will involve a basic application around word cloud. If the reader is able to generate the word cloud, I think we were successful. In the next few chapters, we will learn more about Python as a language, and its features related to process natural language. We will explore some of the basic NLP preprocessing steps and learn about some of basic concepts related to NLP. Chapter 2. Text Wrangling and Cleansing The previous chapter was all about you getting a head start on Python as well as NLTK.
I have used Porter Stemmer most often, and if you are working with English, it's good enough. There is a family of Snowball stemmers that can be used for Dutch, English, French, German, Italian, Portuguese, Romanian, Russian, and so on. com/hindi_stemmer. org/wiki/Stemming. But most users can live with Porter and Snowball stemmer for a large number of use cases. In modern NLP applications, sometimes people even ignore stemming as a pre-processing step, so it typically depends on your domain and application.
You will get to learn over time what kind of pre-processing works best for your corpus, and what can be ignored. In the next chapter will see some of the NLP related pre-processing, like POS tagging, chunking, and NER. I am leaving answers or hints for some of the open questions that we asked in the chapter. Chapter 3. Part of Speech Tagging In previous chapters, we talked about all the preprocessing steps we need, in order to work with any text corpus. You should now be comfortable about parsing any kind of text and should be able to clean it.
Hello World!: Computer Programming for Kids and Other Beginners (2nd Edition) by Warren Sande, Carter Sande