An R Package for Fitting Functional Models to 2-Dimensional Data
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Updated
Jul 23, 2018 - R
An R Package for Fitting Functional Models to 2-Dimensional Data
Python programming labs done throughout the course CSC406 - Artificial Intelligence
A library of functions to perform quantitative analysis of MRI data
Predicted the store level- Global, Division , Department at which the Mean Absolute Percent error is the least for the lift obtained through promotional and baseline sales.
This library gives a modular design for better control of gradient passing between architecture components. Useful for architectures not using a traditional forward and backward pass.
Implemented Traditional ML models for Regression and Classification using sklearn.
stanford university
Assessing the regression problem providing a linear model and a non-linear model.
This repository contains my coursework submissions for the 'Introductory Applied Machine Learning' course.
Statistics for Data Science Assignment
Exemplo de Regressão Linear e Não Linear (BoxCox) utilizando com visualizações gráficas do ggplot.
Predicting concrete compressive strength using GAM regression.
Linear / non-linear regression problem and their comparison and Convolutional Neural Network, Feed Forward Neural Network and their accuracy measurement.
OLS. R and Python. In this project, we study fundamental concepts of Supervised ML models, such as Regression Analysis: Coefficient of Model Adjustment (R²), Parameters Estimation ,Statistical Significance of the Model (F test, T test) ,Multiple Regression , Qualitative Explanatory Variables (X) , heteroscedasticity and etc.
Machine Learning Templates
My personal repository for all of my work for the Statistical Learning and Visualization course at UU in the fall of 2021.
codes for solving minima and least squares fit problems
Builder a nonlinear regression model for estimating the size of some software
Graduation Final Project on electrical engineering (PUC-Rio)
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