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This is a test to ensure the repository and commits are correctly set up
Converting them to a format suitable for machine learning, organizing them into groups, and creating labels
Set-up data loading pipelines for training, validation, and testing
Slight modification to code as error persisted
Completely changed dataset.py as previously it dealt with 2d images, now updated for 3d
define the core components of your recognition model using classes or functions.
Increased Epoch to get high accuracy
Just copied the accuracies from the output file in rangpur and plotted it against the epoch
Testing to see what would give highest accuracy. This gave 0.68
First proper update on readme.md. Still need to add graphs
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This is an initial inspection, no action is required at this point Difficulty: Hard Readme:
Commit messages: good, need more detail on which has been modified instead of just uploading files. Code:
Functionality/Performance:
General comments:
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MarkingGood Practice (Design/Commenting, TF/Torch Usage)Adequate design and implementation Recognition ProblemSolves problem poor performance < 0.6 -1 Commit LogMeaningful commit messages DocumentationReadMe acceptable, no refs -1 Pull RequestSuccessful Pull Request (Working Algorithm Delivered on Time in InCorrect Branch) -2 |
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Feedback marks possible +2 if the requested changes are made (see above). |
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No feedback attempt and no feedback marks granted. |
I had an approved late submission of 1 week, submitting on time. Regards