Implementation of algorithms such as normal equations, gradient descent, stochastic gradient descent, lasso regularization and ridge regularization from scratch and done linear as well as polynomial regression analysis. Implementation of several classification algorithms from scratch i.e. not used any standard libraries like sklearn or tensorflow.

A collection of 8 Applied Data Science projects.

This is a repository for CS4ML. It is a general framework for active learning in regression problems. It approximates a target function arising from general types of data, rather than pointwise samples.

Python implementation of the R stargazer multiple regression model creation tool

Professional resume, portfolio, bio, and presentations for Sean K. Maden, Ph.D.

Spring/Summer 2024 Research - Outside parameters and their effects on COVID-19 Death Totals

Implementação do Trabalho de conclusão de curso, com o tema definido "Aproximação da cinemática inversa de um robô manipulador didático através de algoritmos de aprendizado de máquina"

Modelling and Inference of MICrobiomes Project (MIMIC) is a Python package dedicated to simulate, model, and predict microbial communities interactions

Presentation-Ready Data Summary and Analytic Result Tables

The repository presents a comprehensive project that leverages relevant features to accurately predict the price of Houses.

Laptop Price Prediction

My portfolio website regarding data science projects. Some visualization and analysis projects reflect work for PITAPOLICY clients.

🌌 The R easystats-project

Personal notes during reading "An R Companion to Applied Regression"

pH Level Forecasting of Well Water Samples in Malawi, Conducted by Leeds Beckett University

Statsmodels: statistical modeling and econometrics in Python

This repository contains predictive ml model

📊 Computation and processing of models' parameters

This model utilizes regression models and accurately predicts employee salaries based on experience, previous CTC, and job roles, promoting fair salary structures and optimizing resource allocation for streamlined HR operations.

Multiple Linear Regression