Add t stochastic neighbour embedding using Iris dataset

[Khansa435]

Description:

This PR has added a complete educational workthrough of (t-SNE) t-distributed Stochastic Neighbor Embedding for students.

• Added t-SNE for nonlinear dimensionality reduction.
• Computes high- and low-dimensional affinities (P & Q matrices).
• Uses gradient descent to optimize embeddings.
• Applied on Iris dataset with 2D visualization.
• Includes doctests and clear function structure.

• Add an algorithm?
• Fix a bug or typo in an existing algorithm?
• Add or change doctests? -- Note: Please avoid changing both code and tests in a single pull request.
• Documentation change?

Checklist:

• I have read CONTRIBUTING.md.
• This pull request is all my own work -- I have not plagiarized.
• I know that pull requests will not be merged if they fail the automated tests.
• This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
• All new Python files are placed inside an existing directory.
• All filenames are in all lowercase characters with no spaces or dashes.
• All functions and variable names follow Python naming conventions.
• All function parameters and return values are annotated with Python type hints.
• All functions have doctests that pass the automated testing.
• All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
• If this pull request resolves one or more open issues then the description above includes the issue number(s) with a closing keyword: "Fixes #ISSUE-NUMBER".

[Khansa435]

Hi @cclauss My PR has passed all checks and is marked as “awaiting review”.
Could you please take a look when you have time?

I'm really glad to contribute to this highly maintained repo :)

[cclauss]

Please read about descriptive variable names in CONTRIBUTING.md. Lines like pq = p - q look like they were written in the 1970's and convey nothing to the reader. Single-letter variable names are not accepted in this repository

[Khansa435]

@cclaus Should I remove those "Example " lines from the following code too or just that specific one you mentioned?

[cclauss]

Please remove all instances of Example: and dedent the lines below. The reason is that we have more characters to write our doctests, so we can use ellipses less.

[Nikita-Kedari]

@Khansa435 I have opened Issue for this algorithm and am working on the same

[cclauss]

Add the URL https://en.wikipedia.org/wiki/T-distributed_stochastic_neighbor_embedding to the top of the file to help readers learn.

[Khansa435]

@cclauss Committed all proposed changes (Removed all instances of Example: and dedented the lines below, also added URL at the top of file) and the final commit passes all checks.

Please review the final commit :)

[cclauss]

Awesome!!!

[Khansa435]

Awesome!!!

Thank you so much :)
Your way of guidance is truly commendable.