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Modelled on the popular Learn C Now this is a completely integrated self-study course that is guaranteed to make BASIC programming as fun to use as it is useful to know. Everything needed to learn modelled, structured programming is on the three disks included
Forget the 10,000 hour rule— what if it’s possible to learn the basics of any new skill in 20 hours or less? Take a moment to consider how many things you want to learn to do. What’s on your list? What’s holding you back from getting started? Are you worried about the time and effort it takes to acquire new skills—time you don’t have and effort you can’t spare? Research suggests it takes 10,000 hours to develop a new skill. In this nonstop world when will you ever find that much time and energy? To make matters worse, the early hours of prac­ticing something new are always the most frustrating. That’s why it’s difficult to learn how to speak a new language, play an instrument, hit a golf ball, or shoot great photos. It’s so much easier to watch TV or surf the web . . . In The First 20 Hours, Josh Kaufman offers a systematic approach to rapid skill acquisition— how to learn any new skill as quickly as possible. His method shows you how to deconstruct com­plex skills, maximize productive practice, and remove common learning barriers. By complet­ing just 20 hours of focused, deliberate practice you’ll go from knowing absolutely nothing to performing noticeably well. Kaufman personally field-tested the meth­ods in this book. You’ll have a front row seat as he develops a personal yoga practice, writes his own web-based computer programs, teaches himself to touch type on a nonstandard key­board, explores the oldest and most complex board game in history, picks up the ukulele, and learns how to windsurf. Here are a few of the sim­ple techniques he teaches: Define your target performance level: Fig­ure out what your desired level of skill looks like, what you’re trying to achieve, and what you’ll be able to do when you’re done. The more specific, the better. Deconstruct the skill: Most of the things we think of as skills are actually bundles of smaller subskills. If you break down the subcompo­nents, it’s easier to figure out which ones are most important and practice those first. Eliminate barriers to practice: Removing common distractions and unnecessary effort makes it much easier to sit down and focus on deliberate practice. Create fast feedback loops: Getting accu­rate, real-time information about how well you’re performing during practice makes it much easier to improve. Whether you want to paint a portrait, launch a start-up, fly an airplane, or juggle flaming chain­saws, The First 20 Hours will help you pick up the basics of any skill in record time . . . and have more fun along the way.
Small Basic is a free, beginner-friendly programming language created by Microsoft. Inspired by BASIC, which introduced programming to millions of first-time PC owners in the 1970s and 1980s, Small Basic is a modern language that makes coding simple and fun. Learn to Program with Small Basic introduces you to the empowering world of programming. You’ll master the basics with simple activities like displaying messages and drawing colorful pictures, and then work your way up to programming games! Learn how to: –Program your computer to greet you by name –Make a game of rock-paper-scissors using If/Else statements –Create an interactive treasure map using arrays –Draw intricate geometric patterns with just a few lines of code –Simplify complex programs by breaking them into bite-sized subroutines You’ll also learn to command a turtle to draw shapes, create magical moving text, solve math problems quickly, help a knight slay a dragon, and more! Each chapter ends with creative coding challenges so you can take your skills to the next level. Learn to Program with Small Basic is the perfect place to start your computer science journey.
A basic text, with CD-ROM, for novice users, explaining how to quickly design user interface and build code for Microsoft Windows 95-based applications. Coverage includes the Visual Basic programming environment; toolbox controls drag and drop and animation features; and working with bitmaps and dat
This purchase on Amazon is for JUST THE PAPERBOOK. If you'd like the audiobook please go to: LearnGarifunaNow.com. All products are available there. ---- Luz F. Soliz-Ramos became motivated to create Learn Garifuna Now! when she realized that many Garifuna people, especially the youngsters are not speaking language. The book and its accompanying audio version was created with a fun and easy to follow approach. This will help beginners, intermediate speakers, and all people who want how to jumpstart their ability to speak the Garifuna language in real, every day conversations!
Lots of piano books offer either in-depth analysis or quick gimmicks that don’t really teach music theory. But The Only Basic Piano Instruction Book You’ll Ever Need is different. For students who want to learn the basics and dive right into playing, this book skips all the unnecessary trivia on the history of pianos and avoids lengthy digressions on classical and contemporary musicians. Instead, it focuses specifically on piano instruction and includes: The basics of musical terms, definitions, note-reading structure, and time and key signatures The foundations for chords and more complicated note constructs Exercises and sample pieces of music that range from playing simple notes to combining harmony and melody Perfect even for those starting from scratch, The Only Basic Piano Book You’ll Ever Need makes learning to play a cinch.
An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives. “Written by three experts in the field, Deep Learning is the only comprehensive book on the subject.” —Elon Musk, cochair of OpenAI; cofounder and CEO of Tesla and SpaceX Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning. The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models. Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.
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
A complete self-study course containing information on program design concepts, writing Basic programs and debugging advice for the novice programmer.