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Coding All-in-One For Dummies

Book Description

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

    1. Cover
    2. Introduction
      1. About This Book
      2. Foolish Assumptions
      3. Icons Used in This Book
      4. Beyond the Book
      5. Where to Go from Here
    3. Book 1: Getting Started with Coding
      1. Chapter 1: What Is Coding?
        1. Defining What Code Is
        2. Understanding What Coding Can Do for You
        3. Surveying the Types of Programming Languages
        4. Taking a Tour of a Web App Built with Code
      2. Chapter 2: Programming for the Web
        1. Displaying Web Pages on Your Desktop and Mobile Device
        2. Coding Web Applications
        3. Coding Mobile Applications
      3. Chapter 3: Becoming a Programmer
        1. Writing Code Using a Process
        2. Picking Tools for the Job
    4. Book 2: Career Building with Coding
      1. Chapter 1: Exploring Coding Career Paths
        1. Augmenting Your Existing Job
        2. Finding a New Coding Job
      2. Chapter 2: Exploring Undergraduate and Graduate Degrees
        1. Getting a College Degree
        2. Enrolling in an Advanced Degree Program
        3. Interning to Build Credibility
      3. Chapter 3: Training on the Job
        1. Taking a Work Project to the Next Level
        2. Learning on the Job and after Work
        3. Freelancing to Build Confidence and Skills
        4. Transitioning to a New Role
      4. Chapter 4: Coding Career Myths
        1. Educational Myths
        2. Career Myths
    5. Book 3: Basic Web Coding
      1. Chapter 1: Exploring Basic HTML
        1. What Does HTML Do?
        2. Understanding HTML Structure
        3. Getting Familiar with Common HTML Tasks and Tags
        4. Styling Me Pretty
        5. Building Your First Website Using HTML
      2. Chapter 2: Getting More Out of HTML
        1. Organizing Content on the Page
        2. Listing Data
        3. Putting Data in Tables
        4. Filling Out Forms
        5. Practicing More with HTML
      3. Chapter 3: Getting Stylish with CSS
        1. What Does CSS Do?
        2. CSS Structure
        3. Common CSS Tasks and Selectors
        4. Styling Me Pretty
      4. Chapter 4: Next Steps with CSS
        1. Styling (More) Elements on Your Page
        2. Selecting Elements to Style
        3. Aligning and Laying Out Your Elements
        4. Writing More Advanced CSS
      5. Chapter 5: Building Floating Page Layouts
        1. Creating a Basic Two-Column Design
        2. Building a Three-Column Design
        3. Building a Fixed-Width Layout
        4. Building a Centered Fixed-Width Layout
      6. Chapter 6: Using Alternative Positioning
        1. Working with Absolute Positioning
        2. Managing z-index
        3. Building a Page Layout with Absolute Positioning
        4. Creating a More Flexible Layout
        5. Exploring Other Types of Positioning
        6. Flexible Box Layout Model
    6. Book 4: Advanced Web Coding
      1. Chapter 1: Working Faster with Twitter Bootstrap
        1. Figuring Out What Bootstrap Does
        2. Installing Bootstrap
        3. Understanding the Layout Options
        4. Coding Basic Web Page Elements
        5. Build the Airbnb Home Page
      2. Chapter 2: Adding in JavaScript
        1. What Does JavaScript Do?
        2. Understanding JavaScript Structure
        3. Coding Common JavaScript Tasks
        4. Writing Your First JavaScript Program
        5. Working with APIs
        6. Using JavaScript Libraries
      3. Chapter 3: Understanding Callbacks and Closures
        1. What Are Callbacks?
        2. Understanding Closures
        3. Using Closures
      4. Chapter 4: Embracing AJAX and JSON
        1. Working behind the Scenes with AJAX
        2. Putting Objects in Motion with JSON
      5. Chapter 5: jQuery
        1. Writing More and Doing Less
        2. Getting Started with jQuery
        3. The jQuery Object
        4. Is Your Document Ready?
        5. Using jQuery Selectors
        6. Changing Things with jQuery
        7. Events
        8. Effects
        9. AJAX
    7. Book 5: Creating Web Applications
      1. Chapter 1: Building Your Own App
        1. Building a Location-Based Offer App
        2. Following an App Development Process
        3. Planning Your First Web Application
        4. Exploring the Overall Process
        5. Meeting the People Who Bring a Web App to Life
      2. Chapter 2: Researching Your First Web Application
        1. Dividing the App into Steps
        2. Identifying Research Sources
        3. Researching the Steps in the McDuck’s Offer App
        4. Choosing a Solution for Each Step
      3. Chapter 3: Coding and Debugging Your First Web Application
        1. Getting Ready to Code
        2. Coding Your First Web Application
        3. Debugging Your App
    8. Book 6: Selecting Data Analysis Tools
      1. Chapter 1: Wrapping Your Head around Python
        1. What Does Python Do?
        2. Defining Python Structure
        3. Coding Common Python Tasks and Commands
        4. Shaping Your Strings
        5. Building a Simple Tip Calculator Using Python
      2. Chapter 2: Installing a Python Distribution
        1. Choosing a Python Distribution with Machine Learning in Mind
        2. Installing Python on Linux
        3. Installing Python on Mac OS X
        4. Installing Python on Windows
        5. Downloading the Data Sets and Example Code
      3. Chapter 3: Working with Real Data
        1. Uploading, Streaming, and Sampling Data
        2. Accessing Data in Structured Flat-File Form
        3. Sending Data in Unstructured File Form
        4. Managing Data from Relational Databases
        5. Interacting with Data from NoSQL Databases
        6. Accessing Data from the Web
    9. Book 7: Evaluating Data
      1. Chapter 1: Conditioning Your Data
        1. Juggling between NumPy and pandas
        2. Validating Your Data
        3. Manipulating Categorical Variables
        4. Dealing with Dates in Your Data
        5. Dealing with Missing Data
        6. Slicing and Dicing: Filtering and Selecting Data
        7. Concatenating and Transforming
        8. Aggregating Data at Any Level
      2. Chapter 2: Shaping Data
        1. Working with HTML Pages
        2. Working with Raw Text
        3. Using the Bag of Words Model and Beyond
        4. Working with Graph Data
      3. Chapter 3: Getting a Crash Course in MatPlotLib
        1. Starting with a Graph
        2. Setting the Axis, Ticks, Grids
        3. Defining the Line Appearance
        4. Using Labels, Annotations, and Legends
      4. Chapter 4: Visualizing the Data
        1. Choosing the Right Graph
        2. Creating Advanced Scatterplots
        3. Plotting Time Series
        4. Plotting Geographical Data
        5. Visualizing Graphs
      5. Chapter 5: Exploring Data Analysis
        1. The EDA Approach
        2. Defining Descriptive Statistics for Numeric Data
        3. Counting for Categorical Data
        4. Creating Applied Visualization for EDA
        5. Understanding Correlation
        6. Modifying Data Distributions
      6. Chapter 6: Exploring Four Simple and Effective Algorithms
        1. Guessing the Number: Linear Regression
        2. Moving to Logistic Regression
        3. Making Things as Simple as Naïve Bayes
        4. Learning Lazily with Nearest Neighbors
    10. Book 8: Essentials of Machine Learning
      1. Chapter 1: Introducing How Machines Learn
        1. Getting the Real Story about AI
        2. Learning in the Age of Big Data
      2. Chapter 2: Demystifying the Math behind Machine Learning
        1. Working with Data
        2. Exploring the World of Probabilities
        3. Describing the Use of Statistics
      3. Chapter 3: Descending the Right Curve
        1. Interpreting Learning as Optimization
        2. Exploring Cost Functions
        3. Descending the Error Curve
        4. Updating by Mini-Batch and Online
      4. Chapter 4: Validating Machine Learning
        1. Checking Out-of-Sample Errors
        2. Getting to Know the Limits of Bias
        3. Keeping Model Complexity in Mind
        4. Keeping Solutions Balanced
        5. Training, Validating, and Testing
        6. Resorting to Cross-Validation
        7. Looking for Alternatives in Validation
        8. Optimizing Cross-Validation Choices
        9. Avoiding Sample Bias and Leakage Traps
    11. Book 9: Applying Machine Learning
      1. Chapter 1: Starting with Simple Learners
        1. Discovering the Incredible Perceptron
        2. Growing Greedy Classification Trees
        3. Taking a Probabilistic Turn
      2. Chapter 2: Leveraging Similarity
        1. Measuring Similarity between Vectors
        2. Using Distances to Locate Clusters
        3. Tuning the K-Means Algorithm
        4. Searching for Classification by k-Nearest Neighbors
        5. Leveraging the Correct K Parameter
      3. Chapter 3: Hitting Complexity with Neural Networks
        1. Learning and Imitating from Nature
        2. Struggling with Overfitting
        3. Introducing Deep Learning
      4. Chapter 4: Resorting to Ensembles of Learners
        1. Leveraging Decision Trees
        2. Working with Almost Random Guesses
        3. Boosting Smart Predictors
        4. Averaging Different Predictors
      5. Chapter 5: Real-World Applications
        1. Classifying Images
        2. Scoring Opinions and Sentiments
        3. Using Scoring and Classification
        4. Recommending Products and Movies
    12. About the Authors
    13. Advertisement Page
    14. Connect with Dummies
    15. End User License Agreement