Welcome! The goal of this repository is to provide the implementation from scratch of the most popular machine learning algorithms.

Now you may ask: why should I code from scratch a Logistic Regression if I will use scikit-learn?

Fair enough. However, I would say that it allows to deeply understand the algorithm you're coding, by observing with your own eyes the logic and the relative edge cases. Finally, this can be a fun coding exercise!

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For a theoretical and illustrated overview of these algorithms, please refer to illustrated-machine-learning.github.io

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At the moment you can find:

• K-Means
• K-Nearest Neighbor
• Naive Bayes Classifier
• Logistic Regression
• Linear Regression

To be done:

• Support Vector Machine
• Multi-layer Perceptron
• Decision Tree