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.
Solutions to Coursera's Intro to Machine Learning course in python
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…
Base R Implementation of Logistic Regression from Scratch with Regularization, Laplace Approximation and more
A tool for visualizing the coefficients of various regression models, taking into account empirical data distributions.
Jupyter notebooks implementing Machine Learning algorithms in Scikit-learn and Python
House prices prediction using various regression models.
Implementation of Regularised Logistic Regression Algorithm (Binary Classification only)
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
Ordinal Logistic Regression with ElasticNet Regularization using Multi-Assay Epigenomics Data from CHDI NeuroLINCS Consortium.
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.
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