Completed version of algorithm and README for Problem 8: Classification of ADNI brain data with ConvNeXt like model.(SID 47068591)

[imfatball]

No description provided.

[yexincheng]

This is an initial inspection, no action is required at this point

Recognition Problem : total : 18

1. Solves problem: The solution is appropriate for the problem, achieving an accuracy of 0.802 on the test set.
   The dataset was properly split; subject-level splitting.
   No loss but provided metrics plots. It is weird that validation accuracy is higher than the training.(3/5)
2. Implementation functions: Good (3/3)
3. Good design: Well-designed (1/1)
4. Commenting: Clear and sufficient comments throughout the code. (1/1)
5. Difficulty: Hard (10/10)

Note:

• Pull Request message should include what has been done and the implementations.
• 9 commits happened in three days; some happened after the deadline (Friday, 31 Oct)
• No model description.
• Please add references.

[gayanku]

Marking

Good/OK/Fair Practice (Design/Commenting, TF/Torch Usage)
	Adequate design and implementation.	-1
	Spacing and comments.
	Header blocks.
Recognition Problem
	Good solution to problem.
	Driver Script present.
	File structure present.
	Good Usage & Demo & Visualisation & Data usage.
	Module present.
	Commenting present.
	No Data leakage found.
	Difficulty : Hard. Hard. ConvNeXt
Commit Log
	Good Meaningful commit messages.
	Good Progressive commits.
Documentation
	Readme :Acceptable.	-2
	Model/technical explanation :Good.
	Description and Comments :Good.
	Markdown used and PDF submitted.
Pull Request
	Successful Pull Request (Working Algorithm Delivered on Time in Correct Branch).
	No Feedback required.
	Request Description is missing.	-2
TOTAL		-5

Marked as per the due date and changes after which aren't necessarily allowed to contribute to grade for fairness.
Subject to approval from Shakes