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Algorithms for a beginner to learn and implement Machine Learning

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Machine-learning

Important Algorithms for a beginner to learn and implement Machine Learning:

Linear Regression Logistic Regression K-Nearest Neighbours K-Means Clustering Naive Bayes SVMs Decision Trees Random Forest Dimensionality Reduction Algorithms Gradient Boosting algorithms- XGBoost.

This Repository was a part of the following Open Source Program

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Hacktoberfest 2021

Event details :

  • Hacktoberfest® is open to everyone . Whether you’re a developer, student learning to code, event host, or company of any size, you can help drive growth of open source and make positive contributions to an ever-growing community.
  • All backgrounds and skill levels are encouraged to complete the challenge.
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HacktoberFest Rules :

  • To earn your Hacktoberfest tee or tree reward, you must register and make four valid pull requests (PRs) between October 1-31 (in any time zone).
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  • This year, the first 55,000 participants who successfully complete the challenge will be eligible to receive a prize.

Whether it’s your first or fiftieth pull request, there’s always more to learn! We’ve put together a few resources that can help you create quality pull requests, keep your repositories pristine, and build on your open source knowledge.


Contributing

This repository is contribution friendly. If you'd like to add or improve any algorithm, your contribution is welcome!
Don't forget to follow Contribution Guidelines 😃

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Thanks to all the contributors ❤️

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