updating the first ml project

[ak-0283]

Related Issue

[Cite any related issue(s) this pull request addresses. If none, simply state "None”]

Finishing the issue #4860

Description

This pull request introduces the first Machine Learning project to the repository — a Crop Recommendation System.
The system uses data-driven insights to recommend the most suitable crop based on environmental parameters such as nitrogen, phosphorus, potassium, temperature, humidity, pH, and rainfall.\

The project includes:

• A trained ML model (using algorithms like Random Forest or Decision Tree).
• A user interface for inputting agricultural data and receiving predictions.
• Proper documentation explaining the dataset, preprocessing steps, model training, and usage.
• Visualization of important data insights and model performance metrics.

Type of PR

• Feature enhancement
• Documentation update

Screenshots / Videos (if applicable)

After

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Before

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Checklist

• I have performed a self-review of my code.
• I have read and followed the Contribution Guidelines.
• I have tested the changes thoroughly before submitting this pull request.
• I have provided relevant issue numbers, screenshots, and videos after making the changes.
• I have commented my code, particularly in hard-to-understand areas.
• I have followed the code style guidelines of this project.
• I have checked for any existing open issues that my pull request may address.
• I have ensured that my changes do not break any existing functionality.
• Each contributor is allowed to create a maximum of 4 issues per day. This helps us manage and address issues efficiently.
• I have read the resources for guidance listed below.
• I have followed security best practices in my code changes.

Additional Context

This marks the successful addition of the first ML-based project to the repository, expanding the project scope beyond documentation and front-end development. The Crop Recommendation System demonstrates how machine learning can be applied effectively in agriculture to improve productivity and decision-making.

Resources for Guidance

• Code Harbor Hub Community Features
• Docusaurus Documentation
• React.js Documentation
• Markdown Guide
• MDX Documentation
• Mermaid Documentation

Resources for DSA Features on Our Site:

• Tabs: Switch Languages
• Line Numbering
• Math Equations

Contribution Level

This contribution qualifies as a Level 2 task, as it introduces a new, working ML feature to the project with documentation and testing.

Contribution Guidelines Summary

This project adheres to Code Harbor Hub’s structured contribution levels, and this PR represents a Feature Enhancement with educational and practical value for contributors and learners alike.

Thank you for reviewing my submission!

[deepsource-io]

Here's the code health analysis summary for commits d4b32b1..e341dd6. View details on DeepSource ↗.

Analysis Summary

Analyzer	Status	Summary	Link
JavaScript	✅ Success		View Check ↗

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[ak-0283]

Please review and merge it. @ajay-dhangar

[github-actions]

Hi @ak-0283! 👋 Thank you for submitting your first pull request to CodeHarborHub. Great job on the contribution! 🎉 We appreciate your efforts and our team will review it soon. If you have any questions or need further assistance, feel free to reach out. Keep up the great work!

[github-actions]

Great job, @ak-0283! 🎉 Thank you for submitting your pull request to CodeHarborHub. We appreciate your contribution and enthusiasm! Our team will review it soon. If you have any questions or need further assistance, feel free to reach out. Thanks for contributing!

[github-actions]

⚡️ Lighthouse Report for the Deploy Preview of this PR 🚀

🔗 Site: CodeHarborHub | Live Site

URL 🌐	Performance	Accessibility	Best Practices	SEO	📊
/	🔴 28	🟡 81	🟡 75	🟢 100	📄
/docs	🟡 54	🟢 92	🟡 75	🟢 100	📄
/courses	🟡 59	🟢 92	🟢 96	🟢 100	📄
/showcase	🟡 52	🟢 91	🟡 75	🟡 86	📄
/community	🟡 59	🟢 92	🟢 96	🟢 100	📄

[ajay-dhangar]

Thanks for the contributions to this project; the changes look good and I am happy to approve the merge.