Applied Metaphors: Learning TRIZ, Complexity, Data/Stats/ML using Metaphors
  1. Teaching
  2. Data Analytics for Managers and Creators
  3. Predictive Modelling
  4. 🐉 Intro to Orange
  • Teaching
    • Data Analytics for Managers and Creators
      • Tools
        • Introduction to R and RStudio
        • Introduction to Radiant
        • Introduction to Orange
      • Descriptive Analytics
        • Data
        • Summaries
        • Counts
        • Quantities
        • Groups
        • Densities
        • Groups and Densities
        • Change
        • Proportions
        • Parts of a Whole
        • Evolution and Flow
        • Ratings and Rankings
        • Surveys
        • Time
        • Space
        • Networks
        • Experiments
        • Miscellaneous Graphing Tools, and References
      • Statistical Inference
        • 🧭 Basics of Statistical Inference
        • 🎲 Samples, Populations, Statistics and Inference
        • Basics of Randomization Tests
        • 🃏 Inference for a Single Mean
        • 🃏 Inference for Two Independent Means
        • 🃏 Inference for Comparing Two Paired Means
        • Comparing Multiple Means with ANOVA
        • Inference for Correlation
        • 🃏 Testing a Single Proportion
        • 🃏 Inference Test for Two Proportions
      • Inferential Modelling
        • Modelling with Linear Regression
        • Modelling with Logistic Regression
        • 🕔 Modelling and Predicting Time Series
      • Predictive Modelling
        • 🐉 Intro to Orange
        • ML - Regression
        • ML - Classification
        • ML - Clustering
      • Prescriptive Modelling
        • 📐 Intro to Linear Programming
        • 💭 The Simplex Method - Intuitively
        • 📅 The Simplex Method - In Excel
      • Workflow
        • Facing the Abyss
        • I Publish, therefore I Am
      • Case Studies
        • Demo:Product Packaging and Elderly People
        • Ikea Furniture
        • Movie Profits
        • Gender at the Work Place
        • Heptathlon
        • School Scores
        • Children's Games
        • Valentine’s Day Spending
        • Women Live Longer?
        • Hearing Loss in Children
        • California Transit Payments
        • Seaweed Nutrients
        • Coffee Flavours
        • Legionnaire’s Disease in the USA
        • Antarctic Sea ice
        • William Farr's Observations on Cholera in London
    • R for Artists and Managers
      • 🕶 Lab-1: Science, Human Experience, Experiments, and Data
      • Lab-2: Down the R-abbit Hole…
      • Lab-3: Drink Me!
      • Lab-4: I say what I mean and I mean what I say
      • Lab-5: Twas brillig, and the slithy toves…
      • Lab-6: These Roses have been Painted !!
      • Lab-7: The Lobster Quadrille
      • Lab-8: Did you ever see such a thing as a drawing of a muchness?
      • Lab-9: If you please sir…which way to the Secret Garden?
      • Lab-10: An Invitation from the Queen…to play Croquet
      • Lab-11: The Queen of Hearts, She Made some Tarts
      • Lab-12: Time is a Him!!
      • Iteration: Learning to purrr
      • Lab-13: Old Tortoise Taught Us
      • Lab-14: You’re are Nothing but a Pack of Cards!!
    • ML for Artists and Managers
      • 🐉 Intro to Orange
      • ML - Regression
      • ML - Classification
      • ML - Clustering
      • 🕔 Modelling Time Series
    • TRIZ for Problem Solvers
      • I am Water
      • I am What I yam
      • Birds of Different Feathers
      • I Connect therefore I am
      • I Think, Therefore I am
      • The Art of Parallel Thinking
      • A Year of Metaphoric Thinking
      • TRIZ - Problems and Contradictions
      • TRIZ - The Unreasonable Effectiveness of Available Resources
      • TRIZ - The Ideal Final Result
      • TRIZ - A Contradictory Language
      • TRIZ - The Contradiction Matrix Workflow
      • TRIZ - The Laws of Evolution
      • TRIZ - Substance Field Analysis, and ARIZ
    • Math Models for Creative Coders
      • Maths Basics
        • Vectors
        • Matrix Algebra Whirlwind Tour
        • content/courses/MathModelsDesign/Modules/05-Maths/70-MultiDimensionGeometry/index.qmd
      • Tech
        • Tools and Installation
        • Adding Libraries to p5.js
        • Using Constructor Objects in p5.js
      • Geometry
        • Circles
        • Complex Numbers
        • Fractals
        • Affine Transformation Fractals
        • L-Systems
        • Kolams and Lusona
      • Media
        • Fourier Series
        • Additive Sound Synthesis
        • Making Noise Predictably
        • The Karplus-Strong Guitar Algorithm
      • AI
        • Working with Neural Nets
        • The Perceptron
        • The Multilayer Perceptron
        • MLPs and Backpropagation
        • Gradient Descent
      • Projects
        • Projects
    • Data Science with No Code
      • Data
      • Orange
      • Summaries
      • Counts
      • Quantity
      • 🕶 Happy Data are all Alike
      • Groups
      • Change
      • Rhythm
      • Proportions
      • Flow
      • Structure
      • Ranking
      • Space
      • Time
      • Networks
      • Surveys
      • Experiments
    • Tech for Creative Education
      • 🧭 Using Idyll
      • 🧭 Using Apparatus
      • 🧭 Using g9.js
    • Literary Jukebox: In Short, the World
      • Italy - Dino Buzzati
      • France - Guy de Maupassant
      • Japan - Hisaye Yamamoto
      • Peru - Ventura Garcia Calderon
      • Russia - Maxim Gorky
      • Egypt - Alifa Rifaat
      • Brazil - Clarice Lispector
      • England - V S Pritchett
      • Russia - Ivan Bunin
      • Czechia - Milan Kundera
      • Sweden - Lars Gustaffsson
      • Canada - John Cheever
      • Ireland - William Trevor
      • USA - Raymond Carver
      • Italy - Primo Levi
      • India - Ruth Prawer Jhabvala
      • USA - Carson McCullers
      • Zimbabwe - Petina Gappah
      • India - Bharati Mukherjee
      • USA - Lucia Berlin
      • USA - Grace Paley
      • England - Angela Carter
      • USA - Kurt Vonnegut
      • Spain-Merce Rodoreda
      • Israel - Ruth Calderon
      • Israel - Etgar Keret
  • Posts
  • Blogs and Talks

On this page

  • Introduction to Orange
  • Installing Orange
  • Basic Usage of Orange
  • Orange Workflows
  • Widgets and Channels
  • Loading data into Orange
  • Simple Visuals using Orange
  • Reference
  1. Teaching
  2. Data Analytics for Managers and Creators
  3. Predictive Modelling
  4. 🐉 Intro to Orange

🐉 Intro to Orange

Author

Arvind Venkatadri

Published

October 17, 2022

Modified

May 21, 2024

Abstract
Using A Visual drag and drop tool called Orange

Introduction to Orange

Orange is a visual drag-and-drop tool for

  • Data visualization
  • Machine Learning
  • Data mining

and much more. Here is what it looks like:

All operations are done using a visual menu-driven interface. The visuals can be exported to PNG/SVG/PDF and the entire workflow can be exported into a Report Form and edited for presentation and sharing.

Installing Orange

You can download and install Orange from here:

https://orangedatamining.com/download/

Basic Usage of Orange

Orange Workflows

Widgets and Channels

Loading data into Orange

We are good to get started with Orange!!

Simple Visuals using Orange

Let us create some simple visualizations using Orange.

  • Use the File Widget to import the iris dataset into your session
  • Use the Data Table Widget to look at the data, and note its variable names
  • Use the Visualization Widgets ( Scatter Plot, Bar Plot, and Distributions) to look at the properties of the variables, and examine relationships between them.

Reference

  1. Introduction to Data Mining-Working notes for the hands-on course with Orange Data Mining. (Download file)
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Predictive Modelling
ML - Regression

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