4 1 / 4 O + H 75% CS6310- Software Architecture & Design Assignment #1 [100...
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4 1 / 4 O + H 75% CS6310- Software Architecture & Design Assignment #1 [100 points]: Dataflow Architectures with Orange Data Mining (v1) Spring Term 2024 - created by the CS6310 Instructional Team 14 Submission Deliverables This assignment must be completed individually. You must submit the following items in Canvas: (1) A PDF file named dataflow_report.pdf that contains your two-to six-page (6 pages maximum) report discussing the motivation, structure, and results of your efforts. (2) An Orange Workflow System (OWS) file named dataflow_system.ows that contains your functional and populated Orange Data Mining System. Formats other than PDF and OWS must be pre-approved by an instructor or TA. You must notify us via a private post on Canvas and/or Ed Discussion BEFORE the Due Date if you are encountering difficulty submitting your project. You will not be penalized for situations where Canvas is encountering significant technical problems. However, you must alert us before the due date - not well after the fact. You are responsible for submitting your answers on time in all other cases. Uploading files to Canvas occasionally takes a significantly long time, especially based on the relative size of the files being submitted. Please plan accordingly, as submissions outside of the Canvas Availability Date will likely not be accepted. You are permitted - and highly recommended to take advantage of the opportunity to submit your files an unlimited number of times. Use the same file naming standards for your (optional) "interim submissions" that you do for the final submission. 0 0. Problem Scenario You must find a data set that interests you, and then use the features of the Orange Data Mining System to investigate a relevant clustering, prediction-based and/or pattern discovery result. You are not required (nor intended) to become a data science expert during this assignment; rather, the goal is for you to work with a system that is likely very different from the imperative and object-oriented text-based coding styles that you have probably used extensively. Recommended Steps [1] Select and download a valid data set from a publicly available data set [2] Download the Orange Data Mining software from their website INTEREST [3] Use the Orange Data Mining System to explore your selected data set [4] Provide your results and discoveries in a written report (detailed requirements below) Download and Investigate a Valid Data Set [~15% of the total score] Select a publicly available data set for your use. You may access any of the following websites: https://data.gov/ https://www.tableau.com/learn/articles/free-public-data-sets https://datahub.io/collections https://www.earthdata.nasa.gov/ https://data.fivethirtyeight.com/ https://archive.ics.uci.edu/datasets 4 1 / 4 O + H 75% CS6310- Software Architecture & Design Assignment #1 [100 points]: Dataflow Architectures with Orange Data Mining (v1) Spring Term 2024 - created by the CS6310 Instructional Team 14 Submission Deliverables This assignment must be completed individually. You must submit the following items in Canvas: (1) A PDF file named dataflow_report.pdf that contains your two-to six-page (6 pages maximum) report discussing the motivation, structure, and results of your efforts. (2) An Orange Workflow System (OWS) file named dataflow_system.ows that contains your functional and populated Orange Data Mining System. Formats other than PDF and OWS must be pre-approved by an instructor or TA. You must notify us via a private post on Canvas and/or Ed Discussion BEFORE the Due Date if you are encountering difficulty submitting your project. You will not be penalized for situations where Canvas is encountering significant technical problems. However, you must alert us before the due date - not well after the fact. You are responsible for submitting your answers on time in all other cases. Uploading files to Canvas occasionally takes a significantly long time, especially based on the relative size of the files being submitted. Please plan accordingly, as submissions outside of the Canvas Availability Date will likely not be accepted. You are permitted - and highly recommended to take advantage of the opportunity to submit your files an unlimited number of times. Use the same file naming standards for your (optional) "interim submissions" that you do for the final submission. 0 0. Problem Scenario You must find a data set that interests you, and then use the features of the Orange Data Mining System to investigate a relevant clustering, prediction-based and/or pattern discovery result. You are not required (nor intended) to become a data science expert during this assignment; rather, the goal is for you to work with a system that is likely very different from the imperative and object-oriented text-based coding styles that you have probably used extensively. Recommended Steps [1] Select and download a valid data set from a publicly available data set [2] Download the Orange Data Mining software from their website INTEREST [3] Use the Orange Data Mining System to explore your selected data set [4] Provide your results and discoveries in a written report (detailed requirements below) Download and Investigate a Valid Data Set [~15% of the total score] Select a publicly available data set for your use. You may access any of the following websites: https://data.gov/ https://www.tableau.com/learn/articles/free-public-data-sets https://datahub.io/collections https://www.earthdata.nasa.gov/ https://data.fivethirtyeight.com/ https://archive.ics.uci.edu/datasets
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Income Tax Fundamentals 2013
ISBN: 9781285586618
31st Edition
Authors: Gerald E. Whittenburg, Martha Altus Buller, Steven L Gill
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