Coding All-in-One For Dummies
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Coding All-in-One For Dummies

Coding All-in-One For Dummies


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About the Book

See all the things coding can accomplish The demand for people with coding know-how exceeds the number of people who understand the languages that power technology. Coding All-in-One For Dummies gives you an ideal place to start when you're ready to add this valuable asset to your professional repertoire. Whether you need to learn how coding works to build a web page or an application or see how coding drives the data revolution, this resource introduces the languages and processes you'll need to know. Peek inside to quickly learn the basics of simple web languages, then move on to start thinking like a professional coder and using languages that power big applications. Take a look inside for the steps to get started with updating a website, creating the next great mobile app, or exploring the world of data science. Whether you're looking for a complete beginner's guide or a trusted resource for when you encounter problems with coding, there's something for you! Create code for the web Get the tools to create a mobile app Discover languages that power data science See the future of coding with machine learning tools With the demand for skilled coders at an all-time high, Coding All-in-One For Dummies is here to propel coding newbies to the ranks of professional programmers.

Table of Contents:
Introduction 1 About This Book 2 Foolish Assumptions 2 Icons Used in This Book 3 Beyond the Book 4 Where to Go from Here 4 Book 1: Getting Started with Coding 5 Chapter 1: What Is Coding? 7 Defining What Code Is 8 Understanding What Coding Can Do for You 9 Surveying the Types of Programming Languages 13 Taking a Tour of a Web App Built with Code 16 Chapter 2: Programming for the Web 19 Displaying Web Pages on Your Desktop and Mobile Device 20 Coding Web Applications 26 Coding Mobile Applications 28 Chapter 3: Becoming a Programmer 33 Writing Code Using a Process 33 Picking Tools for the Job 38 Book 2: Career Building with Coding 43 Chapter 1: Exploring Coding Career Paths 45 Augmenting Your Existing Job 46 Finding a New Coding Job 52 Chapter 2: Exploring Undergraduate and Graduate Degrees 59 Getting a College Degree 60 Enrolling in an Advanced Degree Program 65 Interning to Build Credibility 68 Chapter 3: Training on the Job 73 Taking a Work Project to the Next Level 74 Learning on the Job and after Work 75 Freelancing to Build Confidence and Skills 79 Transitioning to a New Role 80 Chapter 4: Coding Career Myths 83 Educational Myths 83 Career Myths 87 Book 3: Basic Web Coding 93 Chapter 1: Exploring Basic HTML 95 What Does HTML Do? 95 Understanding HTML Structure 96 Getting Familiar with Common HTML Tasks and Tags 102 Styling Me Pretty 107 Building Your First Website Using HTML 109 Chapter 2: Getting More Out of HTML 113 Organizing Content on the Page 113 Listing Data 115 Putting Data in Tables 118 Filling Out Forms 124 Practicing More with HTML 127 Chapter 3: Getting Stylish with CSS 129 What Does CSS Do? 129 CSS Structure 131 Common CSS Tasks and Selectors 135 Styling Me Pretty 146 Chapter 4: Next Steps with CSS 151 Styling (More) Elements on Your Page 152 Selecting Elements to Style 157 Aligning and Laying Out Your Elements 163 Writing More Advanced CSS 172 Chapter 5: Building Floating Page Layouts 173 Creating a Basic Two-Column Design 173 Building a Three-Column Design 185 Building a Fixed-Width Layout 193 Building a Centered Fixed-Width Layout 196 Chapter 6: Using Alternative Positioning 201 Working with Absolute Positioning 201 Managing z-index 206 Building a Page Layout with Absolute Positioning 208 Creating a More Flexible Layout 212 Exploring Other Types of Positioning 216 Flexible Box Layout Model 221 Book 4: Advanced Web Coding 231 Chapter 1: Working Faster with Twitter Bootstrap 233 Figuring Out What Bootstrap Does 234 Installing Bootstrap 235 Understanding the Layout Options 236 Coding Basic Web Page Elements 243 Build the Airbnb Home Page 247 Chapter 2: Adding in JavaScript 249 What Does JavaScript Do? 249 Understanding JavaScript Structure 251 Coding Common JavaScript Tasks 253 Writing Your First JavaScript Program 263 Using JavaScript Libraries 267 Chapter 3: Understanding Callbacks and Closures 269 What Are Callbacks? 269 Understanding Closures 274 Using Closures 277 Chapter 4: Embracing AJAX and JSON 279 Working behind the Scenes with AJAX 279 Putting Objects in Motion with JSON 289 Chapter 5: jQuery 295 Writing More and Doing Less 295 Getting Started with jQuery 296 The jQuery Object 297 Is Your Document Ready? 298 Using jQuery Selectors 298 Changing Things with jQuery 300 Events 302 Effects 305 AJAX 309 Book 5: Creating Web Applications 311 Chapter 1: Building Your Own App 313 Building a Location-Based Offer App 313 Following an App Development Process 315 Planning Your First Web Application 316 Exploring the Overall Process 317 Meeting the People Who Bring a Web App to Life 319 Chapter 2: Researching Your First Web Application 325 Dividing the App into Steps 326 Identifying Research Sources 333 Researching the Steps in the McDuck’s Offer App 335 Choosing a Solution for Each Step 338 Chapter 3: Coding and Debugging Your First Web Application 341 Getting Ready to Code 342 Coding Your First Web Application 342 Debugging Your App 350 Book 6: Selecting Data Analysis Tools 351 Chapter 1: Wrapping Your Head around Python 353 What Does Python Do? 354 Defining Python Structure 355 Coding Common Python Tasks and Commands 357 Shaping Your Strings 363 Building a Simple Tip Calculator Using Python 365 Chapter 2: Installing a Python Distribution 367 Choosing a Python Distribution with Machine Learning in Mind 368 Installing Python on Linux 371 Installing Python on Mac OS X 372 Installing Python on Windows 374 Downloading the Data Sets and Example Code 378 Chapter 3: Working with Real Data 387 Uploading, Streaming, and Sampling Data 388 Accessing Data in Structured Flat-File Form 392 Reading from a text file 393 Reading CSV delimited format 394 Reading Excel and other Microsoft Office files 396 Sending Data in Unstructured File Form 397 Managing Data from Relational Databases 400 Interacting with Data from NoSQL Databases 401 Accessing Data from the Web 402 Book 7: Evaluating Data 405 Chapter 1: Conditioning Your Data 407 Juggling between NumPy and pandas 408 Validating Your Data 409 Manipulating Categorical Variables 414 Dealing with Dates in Your Data 419 Dealing with Missing Data 421 Slicing and Dicing: Filtering and Selecting Data 424 Concatenating and Transforming 426 Aggregating Data at Any Level 430 Chapter 2: Shaping Data 433 Working with HTML Pages 434 Working with Raw Text 436 Using the Bag of Words Model and Beyond 442 Working with Graph Data 447 Chapter 3: Getting a Crash Course in MatPlotLib 451 Starting with a Graph 452 Setting the Axis, Ticks, Grids 455 Defining the Line Appearance 458 Using Labels, Annotations, and Legends 462 Chapter 4: Visualizing the Data 467 Choosing the Right Graph 468 Creating Advanced Scatterplots 475 Plotting Time Series 478 Plotting Geographical Data 481 Visualizing Graphs 483 Chapter 5: Exploring Data Analysis 489 The EDA Approach 490 Defining Descriptive Statistics for Numeric Data 491 Counting for Categorical Data 495 Creating Applied Visualization for EDA 498 Understanding Correlation 504 Modifying Data Distributions 508 Chapter 6: Exploring Four Simple and Effective Algorithms 511 Guessing the Number: Linear Regression 512 Moving to Logistic Regression 515 Making Things as Simple as Naïve Bayes 518 Learning Lazily with Nearest Neighbors 522 Book 8: Essentials of Machine Learning 527 Chapter 1: Introducing How Machines Learn 529 Getting the Real Story about AI 530 Learning in the Age of Big Data 541 Chapter 2: Demystifying the Math behind Machine Learning 553 Working with Data 554 Exploring the World of Probabilities 563 Describing the Use of Statistics 568 Chapter 3: Descending the Right Curve 571 Interpreting Learning as Optimization 572 Exploring Cost Functions 576 Descending the Error Curve 578 Updating by Mini-Batch and Online 581 Chapter 4: Validating Machine Learning 585 Checking Out-of-Sample Errors 586 Getting to Know the Limits of Bias 589 Keeping Model Complexity in Mind 591 Keeping Solutions Balanced 592 Training, Validating, and Testing 595 Resorting to Cross-Validation 596 Looking for Alternatives in Validation 597 Optimizing Cross-Validation Choices 598 Avoiding Sample Bias and Leakage Traps 601 Book 9: Applying Machine Learning 603 Chapter 1: Starting with Simple Learners 605 Discovering the Incredible Perceptron 606 Growing Greedy Classification Trees 610 Taking a Probabilistic Turn 615 Chapter 2: Leveraging Similarity 623 Measuring Similarity between Vectors 624 Using Distances to Locate Clusters 626 Tuning the K-Means Algorithm 630 Searching for Classification by k-Nearest Neighbors 637 Leveraging the Correct K Parameter 638 Chapter 3: Hitting Complexity with Neural Networks 643 Learning and Imitating from Nature 644 Struggling with Overfitting 653 Introducing Deep Learning 657 Chapter 4: Resorting to Ensembles of Learners 661 Leveraging Decision Trees 662 Working with Almost Random Guesses 670 Boosting Smart Predictors 673 Averaging Different Predictors 676 Chapter 5: Real-World Applications 677 Classifying Images 677 Scoring Opinions and Sentiments 691 Using Scoring and Classification 703 Recommending Products and Movies 710 Index 725

About the Author :
Nikhil Abraham is the CFO of Udacity, an education company that teaches technology skills that help launch or advance a career. Prior to joining Udacity, Nik worked at Codecademy where he taught beginning coders across a variety of professions. He is also author of Coding For Dummies and Getting a Coding Job For Dummies.


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Product Details
  • ISBN-13: 9781119363033
  • Publisher: John Wiley & Sons Inc
  • Publisher Imprint: Standards Information Network
  • Language: English
  • ISBN-10: 1119363039
  • Publisher Date: 18 Apr 2017
  • Binding: Digital (delivered electronically)
  • No of Pages: 800


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