Machine Learning Code Implementations in Python
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Updated
May 9, 2024 - Python
Machine Learning Code Implementations in Python
In this project I tried to implement logistic regression and regularized logistic regression by my own and compare performance to sklearn model.
Online peer-to-peer (P2P) lending markets enable individual consumers to borrow from, and lend money to, one another directly. We study the borrower-, loan- and group- related determinants of performance predictability in an online P2P lending market by conceptualizing financial and social strength to predict borrower rate and whether the loan w…
Solutions to Coursera's Intro to Machine Learning course in python
Base R Implementation of Logistic Regression from Scratch with Regularization, Laplace Approximation and more
Jupyter notebooks implementing Machine Learning algorithms in Scikit-learn and Python
Ordinal Logistic Regression with ElasticNet Regularization using Multi-Assay Epigenomics Data from CHDI NeuroLINCS Consortium.
Credit card fraud detection
Machine learning project on a given dataset, the goal was to compare several classification models and pick the best one for the given dataset
Implementation of Regularised Logistic Regression Algorithm (Binary Classification only)
This are my solutions to the course Machine Learning from Coursera by Prof. Andrew Ng
A Mathematical Intuition behind Logistic Regression Algorithm
Gradient descent algorithm from scratch for linear and logistic regression with feature scaling and regularization.
A tool for visualizing the coefficients of various regression models, taking into account empirical data distributions.
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