Computer Science Homework

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MLVAssignmentFeb23.pdf.pdf

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DEGREE: BSc Computer Science and Digitisation Module: Machine Learning and Visualisation

Learner declaration I certify that the work submitted for this assignment is my own and research sources are fully acknowledged.

Harvard Referencing: The Harvard Referencing System must be used. The Wikipedia, UKEssays.com or similar websites must not be used or referenced in your work. Introduction This Module equips learners with the advanced knowledge, skills, and competencies to demonstrate an understanding of basics of computer science and its applications and Use of concepts of information systems to make business decisions

Assignment Title: Basics of Machine Learning and Visualisation

Assignment Type: Set exercise testing practical skills

Word Limit: Weighting: 100% Issue Date: 16/04/2024 Submission Date: 27/06/2024

Feedback Date: 18/07/2024 Plagiarism: When submitting work for assessment, students should be aware of the InterActive/Canvas guidance and regulations in concerning plagiarism. All submissions should be your own, original work. You must submit an electronic copy of your work. Your submission will be electronically checked.

Student signature: Date:

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Learning Outcomes:

Assessment Criteria: Weighting 100%

LO1 Demonstrate the understanding of machine learning and deep learning concepts for problem solving.

LO2 Create reports, dashboards and visualizations using Tableau.

LO3 Implement solution with integrating the applications of machine learning and visualisation for storytelling and prescriptive analytics

Tasks (All tasks are equally weighted):

A MS Excel file is attached to this task.

Choose an appropriate machine learning algorithm for regression to present the relation between years of experience on the salary. Using the selected machine learning algorithm, build the regression model illustrating the dependence of the number of years of experience on the salary. Use Tableau to visualize the regression model's predictions.

Provide a detailed description of the problems encountered during the analysis and how you addressed them. Covered learning outcomes: L01, L02, L03

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GUIDANCE ON ASSESSMENT Allmaterials must be properly referenced under Harvard conventions. The length required is 2500 words with tasks equally weighted. The writing style should be formal academic /

report writing style with in-text referencing to support your comments and observations. Originality, quality of argument and good structure are required. The report should demonstrate sound understanding and ability to apply knowledge and theory of Digital Economy and Transformation. Additional marks being awarded for juxtaposition and insight of issues. GradingCriteria

Generic Criteria Knowledge of contexts, concepts, technologies and processes The extent to which knowledge is demonstrated: relevant contextual or theoretical issues are identified, defined and described

historical or contemporary practices are identified, defined and described

90 - 100 80 - 89 70 - 79 60 - 69 50 - 59 40 - 49 Familiar with fundamental contextual and theoretical issues and critical concepts and their relationship to historical and contemporary practices

30 - 39 0-29

Le ve

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Application of technical and professional skills

The degree to which:

appropriate materials and media are selected, tested and utilised to realise and present ideas and solutions

appropriate technologies, methods and processes are identified, defined and described Understanding through application of knowledge

The degree to which research

methods are demonstrated:

relevant knowledge and information is compared, contrasted, manipulated, translated and interpreted

knowledge and information is selected, analysed, synthesized and evaluated in order to generate creative ideas, solutions, arguments or hypotheses

Rigorous application of a range of research methodologies to projects, problems and hypotheses with evidence of highly focused independent thought and critical analysis

Strong ability to produce a range of creative practices and to critically evaluate them to generate highly effective results

Accomplished and original application of a range of specialist practical and technical skills

Accomplished application of advanced transferable and professional skills to problem solving

Outstanding breadth and depth of knowledge of contextual and theoretical issues, some of which are at the forefront of the discipline, and their relationship to a range of historical and contemporary practices

Extensive knowledge of a range of relevant specialist techniques and processes

Relevant knowledge is systematically and rigorously explored and interpreted when proposing solutions to projects and problems which demonstrate evidence of independent thought

Outstanding ability to analyse and synthesise knowledge to produce original creative practice and to evaluate results

Accomplished and fluent application of specialist practical and technical skills

Outstanding demonstration of transferable and professional skills

Extensive knowledge of relevant and specialist techniques and processes

Outstanding breadth of knowledge of contextual and theoretical issues and critical concepts and their relationship to historical and contemporary practices

Accomplished application of specialist practical and technical skills

Highly effective demonstration of transferable and professional skills

Significant knowledge of relevant specialist techniques and processes

Relevant knowledge is thoroughly explored and interpreted when proposing solutions to projects and problems which demonstrate some evidence of independent thought

Strong ability to analyse and synthesise knowledge to produce creative practice and to evaluate results

A significant breadth of knowledge of contextual and theoretical issues and critical concepts and their relationship to historical and contemporary practices

Strong application of specialist practical and technical skills

Relevant knowledge is thoroughly explored and interpreted when proposing solutions to projects and problems

Confident application of transferable and professional skills

Sound ability to analyse and synthesise knowledge to produce creative practice and to evaluate results

Confident knowledge of a range of contextual and theoretical issues and critical concepts and their relationship to historical and contemporary practices

Confident knowledge of relevant specialist techniques and processes

Sound application of transferable and professional

Sound application of specialist practical and technical skills

Sound knowledge of relevant specialist techniques and processes

Relevant knowledge is competently explored and interpreted when proposing solutions to projects and problems

Sound ability to apply and analyse knowledge to produce creative practice and to evaluate results

Familiar with a range of contextual and theoretical issues and critical concepts and their relationship to historical and contemporary practices

Competent ability to explore and interpret relevant knowledge in seeking solutions to projects and problems

Competent application of specialist practical and technical skills

Competent application of transferable and professional skills

Competent ability to apply and analyse knowledge to produce creative practice

Adequate knowledge of relevant specialist techniques and processes

Limited ability to apply knowledge to produce creative practice

Limited ability to manipulate or interpret relevant knowledge in seeking solutions to projects and problems

Rudimentary application of transferable and professional skills

Rudimentary application of specialist practical and technical skills

Limited knowledge of relevant specialist techniques and processes

Some knowledge of fundamental contextual and theoretical issues and critical concepts and their relationship to historical and contemporary practices

No significant knowledge of fundamental contextual and theoretical issues or critical concepts

Little or no ability to apply knowledge to produce creative practice

Little or no ability to manipulate or interpret relevant knowledge in seeking solutions to projects or problems

Ineffective application of specialist practical and technical skills

Ineffective application of transferable and professional skills

No significant knowledge of relevant specialist techniques or processes

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appropriate technologies, methods and processes are demonstrated transferable, professional skills are effectively demonstrated self management and independent learning are demonstrated

Veryhigh abilityto manage own learning in a sustained manner and critically evaluate own progress making effective use of feedback

Strongability to learn independently and critically evaluate own progress using a wide range of feedback sources

Strong ability to learn independently and critically evaluate own progress

Strongability to learn independently make use of feedback

Sound abilityto learn independently and make effective use of feedback

Evidence of ability to learn independently and make use of feedback

Evidence of a rudimentary ability to learn independently

Limited evidence of ability to learn independently

  • DEGREE: BSc Computer Science and Digitisation Module: Machine Learning and Visualisation
    • Assignment Title: Basics of Machine Learning and Visualisation
    • Student signature:
    • Date:
    • Learner declaration I certify that the work submitted for this assignment is my own and research sources are fully acknowledged.
      • report writing style with in-text referencing to support your comments and observations. Originality, quality of argument and good structure are required. The report should demonstrate sound understanding and ability to apply knowledge and theory of Digital Economy and Transformation. Additional marks being awarded for juxtaposition and insight of issues.
        • 30 - 39
        • 0-29