d4rthm4ul
I have extensive experience coding in Python and R to draw insights from data, to do statistical analysis, predictive modeling and data visualization.
Baku, Azerbaijan
Pinned Repositories
d4rthm4ul
Data-cleaning-and-exploring-intermediate
Imputation and Visualization of a dirty movie data with the help of NumPy, Pandas and Matplotlip libraries.
Data-imputation-and-visualization-intermediate
Imputation and Visualization of a dirty bank data with the help of NumPy, Pandas, Matplotlip and Seaborn libraries.
Data-scraping-Beautiful-Soup-intermediate
Scraping one of the most visited web-site of Azerbaijan with the help of BeautifulSoup library.
ML-Classification-LogReg-SupVecMach-KNN
With the help of Logistic Regression, Support Vector Machine and K-Nearest Neighbors models you can predict a person's income that it will be below or above 50K.
ML-Overfitting-Lasso-and-Ridge-Regression
In this repository you will learn how to handle overfitting with the help of Lasso and Ridge Regression regularizations, also working mechanism of those while using useful charts.
ML-Simple-Linear-Regression-Model
Predicting the price of a house according the USA housing data with the help of Simple Linear Regression Machine Learning model.
ML-Simple-Linear-Regression-Model-Intermediate
Predicting number of confirmed, death and recovered patients because of the covid-19 virus for next the day with the help of Simple Linear Regression Machine Learning model.
R-Cleaning-Exploration-Imputation-Visualization
This repository you are browsing contains intermediate level piece of codes which are useful for cleaning, exploratory analysis, handling of missing data points, outlier detection and different visualization techniques using graphics, ggplot2, tidycharts, ggExtra packages. Also in particular part of the script you can get basic information about SparkR package which is an R package that provides a light-weight frontend to use Apache Spark from R . Do not be shy to fork and make contribute.
Time-Series-Analysis-KATS-Covid-19-Azerbaijan
With the help of a brand new KATS package, we can detect outliers, change points, and build very strong Time Series Analysis models. By inspecting this repository you can get a solid vision of KATS on real Covid-19 data of Azerbaijan.
d4rthm4ul's Repositories
d4rthm4ul/Time-Series-Analysis-KATS-Covid-19-Azerbaijan
With the help of a brand new KATS package, we can detect outliers, change points, and build very strong Time Series Analysis models. By inspecting this repository you can get a solid vision of KATS on real Covid-19 data of Azerbaijan.
d4rthm4ul/Data-imputation-and-visualization-intermediate
Imputation and Visualization of a dirty bank data with the help of NumPy, Pandas, Matplotlip and Seaborn libraries.
d4rthm4ul/d4rthm4ul
d4rthm4ul/Data-cleaning-and-exploring-intermediate
Imputation and Visualization of a dirty movie data with the help of NumPy, Pandas and Matplotlip libraries.
d4rthm4ul/Data-scraping-Beautiful-Soup-intermediate
Scraping one of the most visited web-site of Azerbaijan with the help of BeautifulSoup library.
d4rthm4ul/ML-Classification-LogReg-SupVecMach-KNN
With the help of Logistic Regression, Support Vector Machine and K-Nearest Neighbors models you can predict a person's income that it will be below or above 50K.
d4rthm4ul/ML-Overfitting-Lasso-and-Ridge-Regression
In this repository you will learn how to handle overfitting with the help of Lasso and Ridge Regression regularizations, also working mechanism of those while using useful charts.
d4rthm4ul/ML-Simple-Linear-Regression-Model
Predicting the price of a house according the USA housing data with the help of Simple Linear Regression Machine Learning model.
d4rthm4ul/ML-Simple-Linear-Regression-Model-Intermediate
Predicting number of confirmed, death and recovered patients because of the covid-19 virus for next the day with the help of Simple Linear Regression Machine Learning model.
d4rthm4ul/R-Cleaning-Exploration-Imputation-Visualization
This repository you are browsing contains intermediate level piece of codes which are useful for cleaning, exploratory analysis, handling of missing data points, outlier detection and different visualization techniques using graphics, ggplot2, tidycharts, ggExtra packages. Also in particular part of the script you can get basic information about SparkR package which is an R package that provides a light-weight frontend to use Apache Spark from R . Do not be shy to fork and make contribute.
d4rthm4ul/R-Shiny-Interactive-Histogram
This repository you are browsing contains intermediate level piece of codes which are useful to create a shiny app about how to show normal distributed data using histogram. In this R script you will learn how to create User Interface (UI), server (which contains basics of reactivity) and how to combine these two with shinyApp igniter. Do not be shy to fork and make contribute.