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Resource results for topic: PythonPython AhpAnpLib Tuotorials 1: How to install Tools needed
Level: BeginnerAuthor(s): Creative Decisions FoundationWelcome to Python AhpAnpLib Tutorials! In this first tutorial, we will guide you through the process of installing the essential tools needed on a Mac and a Windows system to work with the Python AhpAnpLib library. Learn how to set up Visual Studio Code and Python to get started with creating AHP...
Read MorePython AhpAnpLib Tuotorials 2: Installing Python AhpAnpLib library
Level: BeginnerAuthor(s): Creative Decisions FoundationWelcome to Python AhpAnpLib Tutorials! In this second episode, we will show you how to install and validate the latest version of the Python AhpAnpLib library. Follow along as we guide you through the installation process step-by-step, ensuring you have the most up-to-date tools for creating AHP/...
Read MorePython AhpAnpLib Tutorials 3-1a: Creating an AHP model in Python from scratch
Level: BeginnerAuthor(s): Creative Decisions FoundationWe'll dive into the step-by-step process of building the AHP model in this tutorial. You'll learn how to define criteria, set up the hierarchy, and export the pairwise comparisons questionnaire template.
Read MorePython AhpAnpLib Tutorial 3-1b: Creating an AHP model in Python from an Excel AHP file
Level: BeginnerAuthor(s): Creative Decisions FoundationIn this tutorial, we will show you how to create an Analytic Hierarchy Process (AHP) model in Python using an existing Excel file with AHP data. We'll guide you through the process of importing the AHP structure and judgments from the Excel file into Python, allowing you to work with the mode...
Read MorePython AhpAnpLib Tutorials 3-2a: Eliciting Judgments using an Excel template
Level: BeginnerAuthor(s): Creative Decisions FoundationIn this tutorial, we will demonstrate how to elicit judgments for your Analytic Hierarchy Process (AHP) model using an Excel template. You'll learn how to fill in pairwise comparison matrices and direct values to capture the relative importance of criteria and alternatives. This hands-on guid...
Read MorePython AhpAnpLib Tutorial 3-3: Calculating results
Level: BeginnerAuthor(s): Creative Decisions FoundationIn this tutorial, we dive into the exciting process of calculating results for your Analytic Hierarchy Process (AHP) model. You'll learn how to use the AhpAnpLib library to import your filled-in Excel questionnaire, calculate the pairwise comparison matrices, and derive the priorities of your...
Read MorePython AhpAnpLib Theory 1: Introduction to AHP
Level: BeginnerAuthor(s): Creative Decisions FoundationWelcome to "Theory Tutorial 1: Introduction to AHP"! In this video, Dr. Elena Rokou provides a comprehensive introduction to the Analytic Hierarchy Process (AHP). Developed by Thomas L. Saaty in the 1970s, AHP is a widely-used decision-making framework that helps in complex problem-solvin...
Read MorePython AppAnpLib Tuotorials 3-1c: Creating a model from a super matrix
Level: AdvancedAuthor(s): Creative Decisions FoundationIn this tutorial, we introduce a method of creating models using a supermatrix. with the supermatrix, goal, criteria, subcriteria, and alternatives, connections will be created automatically, and judgments will be read initially for the priority vectors in the supermatrix.
Read MorePython AhpAnpLib Tuotorials 3-1d: Reading SuperDecisions model in Python
Level: AdvancedAuthor(s): Creative Decisions foundationIn this tutorial, we demonstrate a powerful feature that allows users to read SuperDecisions models directly into Python. With this capability, users can seamlessly integrate SuperDecisions models into their Python workflows, enhancing flexibility and efficiency in decision-making processes. All ...
Read MorePython AhpAnpLib Tuotorials 3-5: Sensitivity Analysis
Level: IntermediateAuthor(s): Creative Decisions FoundationIn this tutorial, we delve into the intricacies of sensitivity analysis and its application in the Analytic Hierarchy Process (AHP) and Analytic Network Process (ANP) models. Learn how to evaluate the impact of parameter variations on decision outcomes using the Python AhpAnpLib.
Read More
Python AhpAnpLib Tuotorials 1: How to install Tools needed
Level: BeginnerAuthor(s): Creative Decisions FoundationWelcome to Python AhpAnpLib Tutorials! In this first tutorial, we will guide you through the process of installing the essential tools needed on a Mac and a Windows system to work with the Python AhpAnpLib library. Learn how to set up Visual Studio Code and Python to get started with creating AHP...
Read MorePython AhpAnpLib Tuotorials 2: Installing Python AhpAnpLib library
Level: BeginnerAuthor(s): Creative Decisions FoundationWelcome to Python AhpAnpLib Tutorials! In this second episode, we will show you how to install and validate the latest version of the Python AhpAnpLib library. Follow along as we guide you through the installation process step-by-step, ensuring you have the most up-to-date tools for creating AHP/...
Read MorePython AhpAnpLib Tutorials 3-1a: Creating an AHP model in Python from scratch
Level: BeginnerAuthor(s): Creative Decisions FoundationWe'll dive into the step-by-step process of building the AHP model in this tutorial. You'll learn how to define criteria, set up the hierarchy, and export the pairwise comparisons questionnaire template.
Read MorePython AhpAnpLib Tutorial 3-1b: Creating an AHP model in Python from an Excel AHP file
Level: BeginnerAuthor(s): Creative Decisions FoundationIn this tutorial, we will show you how to create an Analytic Hierarchy Process (AHP) model in Python using an existing Excel file with AHP data. We'll guide you through the process of importing the AHP structure and judgments from the Excel file into Python, allowing you to work with the mode...
Read MorePython AhpAnpLib Tutorials 3-2a: Eliciting Judgments using an Excel template
Level: BeginnerAuthor(s): Creative Decisions FoundationIn this tutorial, we will demonstrate how to elicit judgments for your Analytic Hierarchy Process (AHP) model using an Excel template. You'll learn how to fill in pairwise comparison matrices and direct values to capture the relative importance of criteria and alternatives. This hands-on guid...
Read MorePython AhpAnpLib Tutorial 3-3: Calculating results
Level: BeginnerAuthor(s): Creative Decisions FoundationIn this tutorial, we dive into the exciting process of calculating results for your Analytic Hierarchy Process (AHP) model. You'll learn how to use the AhpAnpLib library to import your filled-in Excel questionnaire, calculate the pairwise comparison matrices, and derive the priorities of your...
Read MorePython AhpAnpLib Theory 1: Introduction to AHP
Level: BeginnerAuthor(s): Creative Decisions FoundationWelcome to "Theory Tutorial 1: Introduction to AHP"! In this video, Dr. Elena Rokou provides a comprehensive introduction to the Analytic Hierarchy Process (AHP). Developed by Thomas L. Saaty in the 1970s, AHP is a widely-used decision-making framework that helps in complex problem-solvin...
Read MorePython AppAnpLib Tuotorials 3-1c: Creating a model from a super matrix
Level: AdvancedAuthor(s): Creative Decisions FoundationIn this tutorial, we introduce a method of creating models using a supermatrix. with the supermatrix, goal, criteria, subcriteria, and alternatives, connections will be created automatically, and judgments will be read initially for the priority vectors in the supermatrix.
Read MorePython AhpAnpLib Tuotorials 3-1d: Reading SuperDecisions model in Python
Level: AdvancedAuthor(s): Creative Decisions foundationIn this tutorial, we demonstrate a powerful feature that allows users to read SuperDecisions models directly into Python. With this capability, users can seamlessly integrate SuperDecisions models into their Python workflows, enhancing flexibility and efficiency in decision-making processes. All ...
Read MorePython AhpAnpLib Tuotorials 3-5: Sensitivity Analysis
Level: IntermediateAuthor(s): Creative Decisions FoundationIn this tutorial, we delve into the intricacies of sensitivity analysis and its application in the Analytic Hierarchy Process (AHP) and Analytic Network Process (ANP) models. Learn how to evaluate the impact of parameter variations on decision outcomes using the Python AhpAnpLib.
Read More