Music Genre Classification

[vybhav72954]

Description

Deep Learning Implementation of Music Genre Classification.

Fixes #576

Type of change

• New feature (non-breaking change which adds functionality)

Checklist:

• My code follows the style guidelines(Clean Code) of this project
• I have performed a self-review of my own code
• I have commented my code, particularly in hard-to-understand areas
• I have created a helpful and easy to understand README.md
• I have made corresponding changes to the documentation
• My changes generate no new warnings
• I have added tests/screenshots(if any) that prove my fix is effective or that my feature works

[HarshCasper]

Few Changes:

• Remove the Database
• Upload the Model File on G-Drive/Dropbox and drop the link here
• Make changes on Python README as well

[HarshCasper]

Since you have already referenced the GTZAN Dataset, do we actually need to store it in the repo as well?

[vybhav72954]

I don't get that, I have just referenced the Repo here, and have stored a file containing 6 features, the whole DB is 1.2 gb.

Can you clarify this?

[vybhav72954]

The size of the csv is also half MB, if you want I can get rid of the file and paste a drive link there

[HarshCasper]

Yeah. The only intent was to get rid of the files that can be retrieved from online sources.

[vybhav72954]

@HarshCasper Would it be fine if I update README in a later PR (not a separate PR but as in when I will solve other issues assigned to me here), I made the branch in my local before the changes in README were made so I still have the older version, also my local is kind of messed up I have multiple upstreams and have kind of lost track (cause i had to test-run my actions somewhere), hence I was planning to remove that local after all my open PRs are merged and clone a fresh one. Would be great if you can allow that.

[vybhav72954]

• Make changes on Python README as well

Fixed in #720

[HarshCasper]

Thanks for the PR!

I am inclined towards merging the same, but can you take a look at the failing checks and the reasons they are failing. As far as I can notice, the Spell Check Action is generating a lot of unnecessary noise. The LinkedIn URL also directs to 999 Status Code, which is understandable since LinkedIn filter requests based on the user-agent. Can you also try looking at the other errors and possibly fix them or raise an Issue to be fixed in these actions?

[vybhav72954]

Can you check #672 @HarshCasper