82 results for “topic:multilinear-regression”
Estudo e implementação dos principais algoritmos de Machine Learning em Jupyter Notebooks.
Predicting the age of abalone using multiple regression in R
Automating Assumption Checks for Regression Models (Work in Progress, Currently Paused)
Project for customer management in the Marketing Analytics Department of a large retail bank. The aim of this project is to know which marketing activity effectively retains customers. We have information about individual customer profitability (CLV) and a survey was conducted as well. A research model explaining/predicting individual customer profitability is expected, along with a theoretical rational for these hypotheses and test the hypotheses. Multiple independent variables very tried to come up with some meaningful conclusions.
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This is a project that contains several techniques of AI to data forecast.
EXCELR ALL ASSIGNMENTS
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practice 2.2 | multilinear regression | automobile company | price prediction
practice 2.1 | multilinear regression | startup companies | profit prediction
My Machine Learning Repository
STAT-420 Methods of Applied Statistics - SUMMER 2017 - UIUC
ml5 (friendly machine learning for the web) SharePoint Framework (SPFx) extension
Prepare a prediction model for profit of 50_startups data. Do transformations for getting better predictions of profit and make a table containing R^2 value for each prepared model.
This repository contains notebook introducing reader to basic concepts of multilinear regression and its application.
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Assignments on ML using Python.........
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By using back propagation algorithm in Multilinear Regression
Demonstrating solving multilinear regression using gradient descent optimisation.
Regression analysis of voice measurements to predict UPDRS scores for people susceptible to Parkinson's Disease
In this post, we develop a Multiple Linear Regression model in Python using the Gradient Descent Algorithm for estimating Model Coefficients to predict the prices of houses in the San Francisco Bay Area.
Colaborate work with Bernhard Hofbauer for our final project in the course "statistische methoden der datenanalyse" in the WS2020
marketing_analyst_MLR
Supervised Learning project aimed at using various features to predict life expectancy.
This project demonstrates the effectiveness of machine learning models in predicting health insurance costs based on individual characteristics and relevant factors. The developed system provides accurate cost estimates, allowing individuals and insurance providers to make informed decisions regarding coverage and premium rates
Practice machine learning from Aurelien Geron's book
Multi Linear Regression - Assignment - 50 Startups
Modelling volume of water consumed by poor people with multilinear regression and multilayer perceptron