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Building Web Applications that Deliver Business Value!
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Course Roadmap - Building Production-Ready Web Apps Fast!
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Why Pricing Products Consistently Is Important
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Course Objective - Product Price Prediction App with Shiny & Flexdashboard
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Resource #1: The Ultimate R Cheat Sheet - Version 2.0 (File Download)
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Installing R (Optional)
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Installing RStudio IDE (Optional)
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Setting Up The Project (File Download)
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Installing R Packages (File Download)
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Transactional Data - What Is It?
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Orders: The Building Blocks of Transactional Data
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Data Model: Entity Relationship Diagram
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Understanding Database Relationships
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Part 1 - Learning Shiny By Building A Sales Dashboard!
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What You Build In This Section
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Resource #2: Flexdashboard Documentation & Key Resources
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Flexdashboard: Introduction & Layout Basics
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Orientation: Column vs Row
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Vertical Layout: Fill vs Scroll
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Tabsets
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Multiple Pages
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Flexdashboard Setup
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Libraries
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Database Connection
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Joining Data Using The SQLite Backend - Part 1
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Joining The Data Using The Database Backend - Part 2
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Processing Data: Final Preparations for the Map
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Adding A Section To The App
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Making the Plotly Map, Part 1: Plotly Chloropleth Maps
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Making The Plotly Map, Part 2: Aggregation By State
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Making The Plotly Map, Part 3: plot_geo()
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Making the Plotly Map, Part 4: add_trace()
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Making the Plotly Map, Part 5: layout()
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What You Build In This Section
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Setup (File Download)
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Resources #3: Shiny Cheat Sheet
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Resource #4: Shiny Widgets Gallery
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Resource #5: HTML Widgets Showcase
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Resource #6: shinyjs
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Shiny Tutorial App - Overview
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Checkbox - checkboxGroupInput()
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Checkbox - renderPrint() & textOutput()
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Date Range - dateRangeInput()
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Date Range - renderPrint() & textOutput()
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Slider - sliderInput()
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Slider - renderPrint() & textOutput()
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Reactive Filtering - reactive()
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Data Table - Interactive Tables with DT
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Reactive Expressions: Adding More Inputs to reactive()
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Reactive Summarization: DT
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Reset Button, Part 1: actionButton()
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Resource #7: Font Awesome
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Reset Button, Part 2: observeEvent()
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Sales Dashboard: Setting Up For Shiny
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shinyWidgets
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Data Preparation
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Bike Type Selector - shinyWidgets::checkboxGroupButtons()
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Bike Type Selector - reactive() & renderPlotly()
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Bike Family Selector - shinyWidgets::pickerInput()
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Bike Family Selector - reactive() filter
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Reset Button: actionButton()
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Challenge 1 - Add Date Range Input (File Download)
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Challenge 1 - Solution, Part 1
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Challenge 1 - Solution, Part 2
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What You Build In this Section
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Setup (File Download)
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Time Series Plot: Game Plan
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Flexdashboard Layout: "Over Time" Section
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Data Preparation
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Making the ggplot Geometries
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Formatting the ggplot
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Adding Interactivity: ggplotly()
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Parameterizing The Time Unit
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Next Steps: Reactivity
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Adding Reactivity: Game Plan
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Adding Reactivity, Part 1: Date Range Input
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Adding Reactivity, Part 2: renderPlotly()
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Adding Reactivity, Part 3: Connecting the Category 1 & 2 Inputs
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Adding Reactivity, Part 4: Date Aggregation with Radio Group Buttons
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Adding Reactivity, Part 5: Connecting the Date Aggregation Buttons
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Finishing Touches
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Next Steps
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Apply Button: Reactive Programming Overview
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Adding the Apply Button: actionButton()
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Reactive Button Click: eventReactive()
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Loading Plots When Firing Up The Application
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Welcome to shinyjs
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Setting Up shinyjs in RMarkdown
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Reset Button: Update Time Aggregation Buttons
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Reset Button: Click "Apply" with shinyjs
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Reset Button: Delay "Apply" Click with shinyjs
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Recap
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What You Build
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Setup & Layout
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Making Value Boxes: valueBox()
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Data Summarization, Part 1
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Data Summarization, Part 2
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Reactive Data Summarization
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Healthy Value Box
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Wealthy Value Box
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Wise Value Box
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Part 2 - Making A Predictive Web Application that Helps Your Organization
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Predictive Analysis Goals
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Setup (File Download)
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Preprocessing the Bikes Table
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Training Data Set: Getting Ready for parsnip + XGBoost
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Machine Learning Algorithm: parsnip + XGBoost
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Modularizing the Preprocessing Code, Part 1: Separate Bike Description
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Modularizing the Preprocessing Code, Part 2: Separate Model Description
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Making Predictions from User Input
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Modularizing the Prediction: Generating New Bikes
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Formatted Table
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Modularizing the Table Output: format_table()
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Bike Prediction Plot: Data Preparation
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Bike Prediction Plot: ggplot, Part 1
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Bike Prediction Plot: ggplot, Part 2
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Modularize the Bike Prediction Plot: plot_bike_prediction()
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What You Build In This Section
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Setup: dir_create() & flexdashboard creation
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Setting Up The Flexdashboard Layout
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Load Libraries
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Data: Connect to SQLite and Load Bikes Table Into Memory
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Scripts: Source Our Modular Prediction Functions
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Machine Learning Model: Loading Our XGBoost Algorithm
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Generating Bike Predictions
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The Prediction Table: format_table()
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The Price Prediction Plot: plot_bike_prediction()
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Aside - The Difference Between Flexdashboard With & Without runtime: shiny
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What You Build In This Section
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Setup (File Download)
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Adding Shiny To Our App - runtime: shiny
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Adding A Text Input: textInput()
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Adding An Apply Button: actionButton()
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Adding Reactivity To The Apply Button: eventReactive()
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Rendering The Prediction Plot: renderPlotly()
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Rendering The Prediction Table: renderTable()
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Render On Load: Prediction Plot & Table
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Challenge #2: Reset Button (File Download)
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Challenge #2 Solution (File Download)
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What You Build In This Section
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Setup (File Download)
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Organizing Our UI & Adding The shinyWidgets Library
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Getting The Unique Categories: distinct()
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Adding Bike Family UI: pickerInput()
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Connecting Bike Family UI To The Apply Button
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Connecting Bike Family UI To The Reset Button
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Generate Bike Type From Bike Family
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Update Bike Family In Bike Prediction
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Adding Frame Material UI: pickerInput()
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Connecting Frame Material UI To Apply, Reset, & Generate New Bike Prediction
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Part 3 - Customizing The App To Your Organizations Brand!
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Setup (File Download)
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Resource #8: Chrome DevTools - Browser Web Development Tools
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CSS Setup & Coloring the Navbar
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Coloring the Sidebar
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Adding a Logo
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Resource #9: Google Fonts
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Navbar - Montserrat
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Headers - Montserrat
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Body - Roboto
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Coloring the Buttons
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Challenge #3: Cannondale Challenge! (File Downloads)
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Challenge #3 Solution, Part 1 (File Download)
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Challenge #3 Solution, Part 2
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Displaying Product Images in Your Shiny App
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Setup (File Downloads)
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Connect the Script & Model Paths
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Image Placeholder
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Extracting the Model Base
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Generate New Bike: To Speed Up Debugging
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Detecting & Retrieving the Image Path
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Expose the Image Path to the App
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Rendering Images: renderImage()
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Handling Bike Models with Numbers in their Names
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Part 4 - Adding Demand Forecasting & Customizing Your Sales Dashboard
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App Setup (File Download)
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Forecast Analysis: Setup & Overview
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Data Processing
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Time Series Aggregation: aggregate_time_series()
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Time Series Plot: plot_time_series()
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Time Series ML vs ARIMA: Why We Are Using ML For Our App
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timetk, Part 1: A toolkit for time series ML prep
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timetk Part 2: A Toolkit for Time Series ML Prep
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Making Training & Future Data
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XGBoost Forecast Model (File Download)
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Making Predictions & Outputting in the Format for Our New Forecast Plot
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Modularizing the XGBoost Forecast: generate_forecast()
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Interactive Forecast Plot
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plot_forecast()
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Visual Forecast Inspection
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Preparing for the Model Change
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Add Logic: Separating the Yearly Data from the Other Time Aggregations
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Making a Linear Regression Model for Yearly Data
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Updating the Plot Forecast Function, Part 1
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Updating the Plot Forecast Function, Part 2
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Saving Our Functions
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Setup (File Download)
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Trend Evaluation
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Experiment #1: Exploring Trend w/ XGBoost Forecast
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Experiment #2: Comparing XGBoost & GLMNet
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Overview
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Setup
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Toggle Switch: switchInput() [with CSS Copy-Paste]
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Showing & Hiding the Forecast Horizon: conditionalPanel()
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Link the Forecast Toggle Switch to Reset & Update Buttons
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Integrating the Forecast
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Producing the Forecast Plot
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Connecting the Forecast to the Time Unit Radio Buttons: observeEvent()
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Connecting the Forecast to the Forecast Mode Toggle Switch: observeEvent()
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Value Boxes, Part 1: Update Colors with Changing Data Filters
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Value Boxes, Part 2: Update Colors with Changing Data Filters
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Customer Selection: pickerInput()
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Connecting the Customer Selection to the Data Filter
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Recap
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Creating a CSS Theme for Our Shiny App
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Setup (File Download)
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Connecting Our CSS & Logo
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Adjusting the Sidebar Width
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Coloring the Forecast Mode Toggle Switch
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Coloring the Time Series Radio Buttons
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Coloring the Value Boxes
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Updating the CSS to Make Responsive for Mobile Devices
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Enabling Scroll Capability on the UI Sidebar for Mobile Devices
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Making a Dark Theme!
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Adding A View Mode Toggle Switch
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Creating The Dark Theme
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Switching Themes with includeCSS() & renderUI()
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Adjusting the Theme for Mobile Devices
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Final Shiny Sales Dashboard with Forecasting & Dark Theme!
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Publishing Your Shiny Web Application
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Publishing Options
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Setup: Shinyapps.io & App Files
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Connecting To Shinyapps.io & Publishing
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Troubleshooting Error #1: Files are Outside of App Directory
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Troubleshooting Error #2: xgboost package is not being installed
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Shiny App Deployed!!!
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Challenge #4: Create & Deploy Your Own App
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You Did It! I'm So Happy For You!!
