Your final write-up should be between 3 – 4 pages. Your final report should include the following:
• Title, Author(s)
• Abstract: It should not be more than 300 words.
• Introduction: This section introduces the problem, and your overall approach to the problem.
• Background/Related Work: This section discusses relevant literature for your project.
• Approach: This section details your approach to the problem. For example, this is the section where you would describe your NLP methods and why the selected metrics should provide better answers for your problem and data. You should be specific – you may want to include equations, figures, plots, etc.
• Experiments: In this section, you describe:
o The dataset(s) you used
o How you ran your experiments (e.g. model configurations, learning rate, training time, etc.)
o The evaluation metric(s) you used
o Your results. show numbers, figures, tables etc. relating to your evaluation metric(s)
o Comparison between the statistical- based and deep learning-based methods. What features (i.e. words) were most indicatives for the analysis in both approaches
• Conclusion: What have you learned? Suggest future ideas.
• References and Team Contribution: Include references to all literature that informed your project work. The contribution of each team member should be added here.
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