Mojmelo v0.1: Machine Learning algorithms in pure Mojo

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I’m happy to announce the release of Mojmelo v0.1; Implementations of Machine Learning algorithms from scratch in pure Mojo: GitHub - yetalit/Mojmelo: Machine Learning algorithms in pure Mojo 🔥

Here is the list of the algorithms:

  • Linear Regression

  • Polynomial Regression

  • Logistic Regression

  • KNN

  • KMeans

  • DBSCAN

  • SVM

  • Naive Bayes

    1. GaussianNB

    2. MultinomialNB

  • Decision Tree (Regression/Classification)

  • Random Forest (Regression/Classification)

  • GBDT (Regression/Classification)

  • PCA

Preprocessing:

  • normalize

  • MinMaxScaler

  • StandardScaler

  • KFold

  • GridSearchCV

  • LabelEncoder

Documentation: https://yetalit.github.io/Mojmelo/docs/_index.html

With version 0.1, the fundamental development phase got completed. Thus, mojmelo is now open to be tested on different user datasets.

Due to some limitations, I haven’t been able to provide user friendly benchmarking results yet. So, if you manage to do some benchmarking, feel free to submit them to the repository (by opening Pull Requests).

Finally, I want to give a huge thanks to everyone who showed interest in or support for the project. It was really motivating along the way :heart:

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This is really nice, great work Doby!

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