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followers: 8.0 following: 11.0 repos: 13.0 gists: 0.0

Name: Ali Mirzaei

Type: User

Bio: Hi! I'm Ali Mirzaei, a data scientist with experience about analysis , prediction and clustering in fields of road accidents and drivers Behaviour with R.

Blog: https://www.linkedin.com/in/ali-mirzaei-8041411b9/

Hi there 👋

I'm Ali Mirzaei known as Senior Data Scientist and expert in:

🔭 Time series data analysis.
🔭 Regression Models for Count Data in R.
🌱 Principal component analysis.
🌱 Nonparametric Regression Models(dditive models, trees and neural networks ) in R.
👯 Generalized Additive Models (GAMs)& Automate the procedures identifying the maximal model (lm,lmer,glm,gam,...).
🤔 I’m currently working on Road accident modeling.
👯 I'm looking to collaborate on machine learning algorithm for accidents prediction.
🤔 I'm currently researching on drivers behaviour for pattern discovery and detection level of risk for roads.

Ali Mirzaei's Projects

alimirzaei1354

buildmer

Automatic model build-up and comparison for mixed-effects and other models

exploratory-data-analysis-tools

A survey of tools that make EDA more automated.

gam

This project is designed to model road accidents based on traffic variables.

generalized-additive-models

A document introducing generalized additive models.📈

generalized-additive-models-workshop-2019

A workshop on using generalized additive models and the mgcv package.

mixed-models-with-r

Covers the basics of mixed models, mostly using @lme4

mixed-models-with-r-workshop-2019

Workshop on using Mixed Models with R

r-iv-visualization

Getting started with pretty pictures in R

regression-models-for-count-data-in-r

road-accident-prediction-with-generalized-additive-models-gams-

This project is designed to model road accidents based on traffic variables. title: "Generalized Additive Models (GAMs)" author: "AliMirzaei" date: "11/20/2022"

text-analysis-with-r

:book: :books: :newspaper: Workshop that demonstrates using and analyzing text in R.

webr

Raw files for a document providing an introduction to web-scraping and beyond in R.

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