Coding All-in-One For Dummies

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. Title Page Copyright Page Table of Contents Introduction About This Book Foolish Assumptions Icons Used in This Book Beyond the Book Where to Go from Here Book 1 Getting Started with Coding Chapter 1 What Is Coding? Defining What Code Is Following instructions Writing code with some Angry Birds Understanding What Coding Can Do for You Eating the world with software Coding on the job Scratching your own itch (and becoming rich and famous) Surveying the Types of Programming Languages Comparing low-level and high-level programming languages Contrasting compiled code and interpreted code Programming for the web Taking a Tour of a Web App Built with Code Defining the app’s purpose and scope Standing on the shoulders of giants Chapter 2 Programming for the Web Displaying Web Pages on Your Desktop and Mobile Device Hacking your favorite news website Understanding how the World Wide Web works Watching out for your front end and back end Defining web and mobile applications Coding Web Applications Starting with HTML, CSS, and JavaScript Adding logic with Python, Ruby, or PHP Coding Mobile Applications Building mobile web apps Building native mobile apps Chapter 3 Becoming a Programmer Writing Code Using a Process Researching what you want to build Designing your app Coding your app Debugging your code Picking Tools for the Job Working offline Working online with Codecademy.com Book 2 Career Building with Coding Chapter 1 Exploring Coding Career Paths Augmenting Your Existing Job Creative design Content and editorial Human resources Product management Sales and marketing Legal Finding a New Coding Job Front-end web development Back-end web development Mobile application development Data analysis Chapter 2 Exploring Undergraduate and Graduate Degrees Getting a College Degree College computer science curriculum Doing extracurricular activities Two-year versus four-year school Enrolling in an Advanced Degree Program Graduate school computer science curriculum Performing research Interning to Build Credibility Types of internship programs Securing an internship Chapter 3 Training on the Job Taking a Work Project to the Next Level Learning on the Job and after Work Training on the job Learning after work Freelancing to Build Confidence and Skills Transitioning to a New Role Assessing your current role Networking with developers Identifying roles that match your interest and skills Chapter 4 Coding Career Myths Educational Myths You must be good at math You must have studied engineering You can learn coding in a few weeks You need a great idea to start coding Ruby is better than Python Career Myths Only college graduates receive coding offers You must have experience Tech companies don’t hire women or minorities The highest paying coding jobs are in San Francisco Your previous experience isn’t relevant Book 3 Basic Web Coding Chapter 1 Exploring Basic HTML What Does HTML Do? Understanding HTML Structure Identifying elements Featuring your best attribute Standing head, title, and body above the rest Getting Familiar with Common HTML Tasks and Tags Writing headlines Organizing text in paragraphs Linking to your (heart’s) content Adding images Styling Me Pretty Highlighting with bold, italics, underline, and strikethrough Raising and lowering text with superscript and subscript Building Your First Website Using HTML Chapter 2 Getting More Out of HTML Organizing Content on the Page Listing Data Creating ordered and unordered lists Nesting lists Putting Data in Tables Basic table structuring Stretching table columns and rows Aligning tables and cells Filling Out Forms Understanding how forms work Creating basic forms Practicing More with HTML Chapter 3 Getting Stylish with CSS What Does CSS Do? CSS Structure Choosing the element to style My property has value Hacking the CSS on your favorite website Common CSS Tasks and Selectors Font gymnastics: Size, color, style, family, and decoration Customizing links Adding background images and styling foreground images Styling Me Pretty Adding CSS to your HTML Building your first web page Chapter 4 Next Steps with CSS Styling (More) Elements on Your Page Styling lists Designing tables Selecting Elements to Style Styling specific elements Naming HTML elements Aligning and Laying Out Your Elements Organizing data on the page Shaping the div Understanding the box model Positioning the boxes Writing More Advanced CSS Chapter 5 Building Floating Page Layouts Creating a Basic Two-Column Design Designing the page Building the HTML Using temporary background colors Setting up the floating columns Tuning up the borders Advantages of a fluid layout Using semantic tags Building a Three-Column Design Styling the three-column page Problems with the floating layout Specifying a min-height Using height and overflow Building a Fixed-Width Layout Setting up the HTML Fixing the width with CSS Building a Centered Fixed-Width Layout Making a surrogate body with an all div How the jello layout works Limitations of the jello layout Chapter 6 Using Alternative Positioning Working with Absolute Positioning Setting up the HTML Adding position guidelines Making absolute positioning work Managing z-index Handling depth Working with z-index Building a Page Layout with Absolute Positioning Overview of absolute layout Writing the HTML Adding the CSS Creating a More Flexible Layout Designing with percentages Building the layout Exploring Other Types of Positioning Creating a fixed menu system Setting up the HTML Setting the CSS values Flexible Box Layout Model Creating a flexible box layout Viewing a flexible box layout . . . And now for a little reality Book 4 Advanced Web Coding Chapter 1 Working Faster with Twitter Bootstrap Figuring Out What Bootstrap Does Installing Bootstrap Understanding the Layout Options Lining up on the grid system Dragging and dropping to a website Using predefined templates Adapting layout for mobile, tablet, and desktop Coding Basic Web Page Elements Designing buttons Navigating with toolbars Adding icons Build the Airbnb Home Page Chapter 2 Adding in JavaScript What Does JavaScript Do? Understanding JavaScript Structure Using semicolons, quotes, parentheses, and braces Coding Common JavaScript Tasks Storing data with variables Making decisions with if-else statements Working with string and number methods Alerting users and prompting them for input Naming code with functions Adding JavaScript to the web page Writing Your First JavaScript Program Working with APIs What do APIs do? Scraping data without an API Researching and choosing an API Using JavaScript Libraries jQuery D3.js Chapter 3 Understanding Callbacks and Closures What Are Callbacks? Passing functions as arguments Writing functions with callbacks Using named callback functions Understanding Closures Using Closures Chapter 4 Embracing AJAX and JSON Working behind the Scenes with AJAX AJAX examples Viewing AJAX in action Using the XMLHttpRequest object Working with the same-origin policy Using CORS, the silver bullet for AJAX requests Putting Objects in Motion with JSON Chapter 5 jQuery Writing More and Doing Less Getting Started with jQuery The jQuery Object Is Your Document Ready? Using jQuery Selectors Changing Things with jQuery Getting and setting attributes Changing CSS Manipulating elements in the DOM Events Using on() to attach events Detaching with off() Binding to events that don’t exist yet Other event methods Effects Basic effects Fading effects Sliding effects Setting arguments for animation methods Custom effects with animate() Playing with jQuery animations AJAX Using the ajax() method Shorthand AJAX methods Book 5 Creating Web Applications Chapter 1 Building Your Own App Building a Location-Based Offer App Understanding the situation Plotting your next steps Following an App Development Process Planning Your First Web Application Exploring the Overall Process Meeting the People Who Bring a Web App to Life Creating with designers Coding with front- and back-end developers Managing with product managers Testing with quality assurance Chapter 2 Researching Your First Web Application Dividing the App into Steps Finding your app’s functionality Finding your app’s functionality: My version Finding your app’s form Finding your app’s form: The McDuck’s Offer App design Identifying Research Sources Researching the Steps in the McDuck’s Offer App Choosing a Solution for Each Step Chapter 3 Coding and Debugging Your First Web Application Getting Ready to Code Coding Your First Web Application Development environment Prewritten code Coding steps for you to follow Debugging Your App Book 6 Selecting Data Analysis Tools Chapter 1 Wrapping Your Head around Python What Does Python Do? Defining Python Structure Understanding the Zen of Python Styling and spacing Coding Common Python Tasks and Commands Defining data types and variables Computing simple and advanced math Using strings and special characters Deciding with conditionals: if, elif, else Input and output Shaping Your Strings Dot notation with upper(), lower(), capitalize(), and strip() String formatting with % Building a Simple Tip Calculator Using Python Chapter 2 Installing a Python Distribution Choosing a Python Distribution with Machine Learning in Mind Getting Continuum Analytics Anaconda Getting Enthought Canopy Express Getting Python(x,y) Getting WinPython Installing Python on Linux Installing Python on Mac OS X Installing Python on Windows Downloading the Data Sets and Example Code Using Jupyter Notebook Defining the code repository Understanding the data sets used in this book Chapter 3 Working with Real Data Uploading, Streaming, and Sampling Data Uploading small amounts of data into memory Streaming large amounts of data into memory Sampling data Accessing Data in Structured Flat-File Form Reading from a text file Reading CSV delimited format Reading Excel and other Microsoft Office files Sending Data in Unstructured File Form Managing Data from Relational Databases Interacting with Data from NoSQL Databases Accessing Data from the Web Book 7 Evaluating Data Chapter 1 Conditioning Your Data Juggling between NumPy and pandas Knowing when to use NumPy Knowing when to use pandas Validating Your Data Figuring out what’s in your data Removing duplicates Creating a data map and data plan Manipulating Categorical Variables Creating categorical variables Renaming levels Combining levels Dealing with Dates in Your Data Formatting date and time values Using the right time transformation Dealing with Missing Data Finding the missing data Encoding missingness Imputing missing data Slicing and Dicing: Filtering and Selecting Data Slicing rows Slicing columns Dicing Concatenating and Transforming Adding new cases and variables Removing data Sorting and shuffling Aggregating Data at Any Level Chapter 2 Shaping Data Working with HTML Pages Parsing XML and HTML Using XPath for data extraction Working with Raw Text Dealing with Unicode Stemming and removing stop words Introducing regular expressions Using the Bag of Words Model and Beyond Understanding the bag of words model Working with n-grams Implementing TF-IDF transformations Working with Graph Data Understanding the adjacency matrix Using NetworkX basics Chapter 3 Getting a Crash Course in MatPlotLib Starting with a Graph Defining the plot Drawing multiple lines and plots Saving your work Setting the Axis, Ticks, Grids Getting the axes Formatting the axes Adding grids Defining the Line Appearance Working with line styles Using colors Adding markers Using Labels, Annotations, and Legends Adding labels Annotating the chart Creating a legend Chapter 4 Visualizing the Data Choosing the Right Graph Showing parts of a whole with pie charts Creating comparisons with bar charts Showing distributions using histograms Depicting groups using boxplots Seeing data patterns using scatterplots Creating Advanced Scatterplots Depicting groups Showing correlations Plotting Time Series Representing time on axes Plotting trends over time Plotting Geographical Data Visualizing Graphs Developing undirected graphs Developing directed graphs Chapter 5 Exploring Data Analysis The EDA Approach Defining Descriptive Statistics for Numeric Data Measuring central tendency Measuring variance and range Working with percentiles Defining measures of normality Counting for Categorical Data Understanding frequencies Creating contingency tables Creating Applied Visualization for EDA Inspecting boxplots Performing t-tests after boxplots Observing parallel coordinates Graphing distributions Plotting scatterplots Understanding Correlation Using covariance and correlation Using nonparametric correlation Considering chi-square for tables Modifying Data Distributions Using the normal distribution Creating a z-score standardization Transforming other notable distributions Chapter 6 Exploring Four Simple and Effective Algorithms Guessing the Number: Linear Regression Defining the family of linear models Using more variables Understanding limitations and problems Moving to Logistic Regression Applying logistic regression Considering when classes are more Making Things as Simple as Naïve Bayes Finding out that Naïve Bayes isn’t so naïve Predicting text classifications Learning Lazily with Nearest Neighbors Predicting after observing neighbors Choosing your k parameter wisely Book 8 Essentials of Machine Learning Chapter 1 Introducing How Machines Learn Getting the Real Story about AI Moving beyond the hype Dreaming of electric sheep Overcoming AI fantasies Considering the relationship between AI and machine learning Considering AI and machine learning specifications Defining the divide between art and engineering Learning in the Age of Big Data Defining big data Considering the sources of big data Specifying the role of statistics in machine learning Understanding the role of algorithms Defining what training means Chapter 2 Demystifying the Math behind Machine Learning Working with Data Creating a matrix Understanding basic operations Performing matrix multiplication Glancing at advanced matrix operations Using vectorization effectively Exploring the World of Probabilities Operating on probabilities Conditioning chance by Bayes’ theorem Describing the Use of Statistics Chapter 3 Descending the Right Curve Interpreting Learning as Optimization Supervised learning Unsupervised learning Reinforcement learning The learning process Exploring Cost Functions Descending the Error Curve Updating by Mini-Batch and Online Chapter 4 Validating Machine Learning Checking Out-of-Sample Errors Looking for generalization Getting to Know the Limits of Bias Keeping Model Complexity in Mind Keeping Solutions Balanced Depicting learning curves Training, Validating, and Testing Resorting to Cross-Validation Looking for Alternatives in Validation Optimizing Cross-Validation Choices Exploring the space of hyper-parameters Avoiding Sample Bias and Leakage Traps Watching out for snooping Book 9 Applying Machine Learning Chapter 1 Starting with Simple Learners Discovering the Incredible Perceptron Falling short of a miracle Touching the nonseparability limit Growing Greedy Classification Trees Predicting outcomes by splitting data Pruning overgrown trees Taking a Probabilistic Turn Understanding Naïve Bayes Estimating response with Naïve Bayes Chapter 2 Leveraging Similarity Measuring Similarity between Vectors Understanding similarity Computing distances for learning Using Distances to Locate Clusters Checking assumptions and expectations Inspecting the gears of the algorithm Tuning the K-Means Algorithm Experimenting K-means reliability Experimenting with how centroids converge Searching for Classification by k-Nearest Neighbors Leveraging the Correct K Parameter Understanding the k parameter Experimenting with a flexible algorithm Chapter 3 Hitting Complexity with Neural Networks Learning and Imitating from Nature Going forth with feed-forward Going even deeper down the rabbit hole Getting back with backpropagation Struggling with Overfitting Understanding the problem Opening the black box Introducing Deep Learning Chapter 4 Resorting to Ensembles of Learners Leveraging Decision Trees Growing a forest of trees Understanding the importance measures Working with Almost Random Guesses Bagging predictors with Adaboost Boosting Smart Predictors Meeting again with gradient descent Averaging Different Predictors Chapter 5 Real-World Applications Classifying Images Working with a set of images Extracting visual features Recognizing faces using eigenfaces Classifying images Scoring Opinions and Sentiments Introducing natural language processing Understanding how machines read Processing and enhancing text Scraping textual data sets from the web Handling problems with raw text Using Scoring and Classification Performing classification tasks Analyzing reviews from e-commerce Recommending Products and Movies Realizing the revolution Downloading rating data Trudging through the MovieLens data set Navigating through anonymous web data Encountering the limits of rating data Leveraging SVD Index EULA