Machine Learning 101: Implementing Logistic Regression and LDA from scratch
What a better way to really understand something than doing it yourself? Here, along with two other teammates, we had the opportunity to implement two famous classic machine learning algorithms: Logistic Regression and LDA, examples of discriminative and generative algorithms, respectively. We also had the opportunity to explore standard ML techniques such as data cleaning, feature engineering, k-fold cross-validation implementation, CV-Grid search, and visualizations.
Our repository:
https://github.com/JairParra/Logreg_LDA_from_scratch
Our paper:
https://drive.google.com/file/d/1Ylg6MuNNjk6fBfCsZLKrxoeye4gG7hGZ/view?usp=sharing
Our repository:
https://github.com/JairParra/Logreg_LDA_from_scratch
Our paper:
https://drive.google.com/file/d/1Ylg6MuNNjk6fBfCsZLKrxoeye4gG7hGZ/view?usp=sharing
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