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COMP1801 Machine Learning

  1. Practical Implementation(complete code, trained model and data to replicate the results).The source code must be error-free.Minimum requirements:
  • Coherent implementation(no errors, sound training pipeline).
  • Appropriate metric(Do not confuse metrics for classification, regression, clustering, dimensionality reduction, etc.).
  • Sound evaluation(comparison with trivial baselines, such as random flipping coin, outputting the most frequent label,outputting the previous value in time series,and existing machine learning methods that can be applied to the topic.).
  1. Written Report (4 pages of a detailed description of the steps taken in carrying out the project.
  • Must follow the template uploaded on the Moodle website.
  • Should include references where appropriate
  • For document structure, please follow the template.

The coursework marking will be based on the report,in principle.The submitted source codes are used,for example,to verify whether the description in the report reflects the implementation and the appropriateness of the implementation but do not have a specific ratio in marking.Even if the implementation is of good quality,it will be ignored if it is not explained well in the report.

Assessment Criteria
  • Quality of the presentation.
  • Logicality of the explanation
  • Adherence to the given format and scientific writing rules
Assessment Criteria:Further details

The quality of the presentation is assessed in terms of whether the students explained all the items described in the template clearly,exactly,sufficiently,and concisely.See the template for detailed information.If your report needs other kinds of descriptions,we also assess their quality.The logicality of the explanation is assessed in terms:-

  • Positioning their work appropriately in the problem domain.
  • Giving scientific reasons why their method can solve the problem.
  • Giving clear reasons why their evaluation method can judge whether their approach has succeeded or not.
  • Fair,objective,and reasonable conclusions and critical review.
  • Logical reasoning for other explanations The adherence to the given format and scientific writing rules is assessed in terms.
  • Basic formats(page size, margin, font size, page limitation, etc.)
  • Following the given template.
  • Correct citation.
  • Conciseness.
  • Consistency.
  • Scientific writing rules.
  • Other formats.

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