Coding Projects

R Programming Roadmap | |-- Fundamentals | |-- Basics of Programming | | |-- Introduction to R | | |-- Setting Up Development Environment (RStudio) | | | |-- Syntax and Structure | | |-- Basic Syntax | | |-- Variables and Data Types | | |-- Operators and Expressions | |-- Control Structures | |-- Conditional Statements | | |-- If-Else Statements | | | |-- Loops | | |-- For Loop | | |-- While Loop | | |-- Repeat Loop | | | |-- Exception Handling | | |-- Try-Catch Block | | |-- Warnings and Errors | |-- Functions and Scope | |-- Defining Functions | | |-- Function Syntax | | |-- Parameters and Arguments | | |-- Return Statement | | | |-- Scope | | |-- Global and Local Scope | | |-- Environments | |-- Data Structures | |-- Vectors | | |-- Creating Vectors | | |-- Vectorized Operations | | | |-- Lists | | |-- Creating and Manipulating Lists | | | |-- Matrices | | |-- Creating Matrices | | |-- Matrix Operations | | | |-- Data Frames | | |-- Creating Data Frames | | |-- Manipulating Data Frames | | | |-- Factors | | |-- Creating and Using Factors | |-- Data Manipulation | |-- dplyr | | |-- Select, Filter, Arrange, Mutate, Summarize | | |-- Piping (%>%) | | | |-- tidyr | | |-- Gather and Spread | | |-- Separate and Unite | |-- Data Visualization | |-- Base R Graphics | | |-- Plot, Hist, Boxplot, Barplot | | | |-- ggplot2 | | |-- Grammar of Graphics | | |-- Creating Plots (Scatter, Line, Bar, Histogram) | | |-- Customizing Plots (Themes, Labels, Legends) | |-- Statistical Analysis | |-- Descriptive Statistics | | |-- Mean, Median, Mode | | |-- Standard Deviation, Variance | | | |-- Inferential Statistics | | |-- Hypothesis Testing (t-tests, ANOVA) | | |-- Correlation and Regression Analysis | |-- Advanced R | |-- Date and Time | | |-- Working with Dates and Times | | |-- lubridate Package | | | |-- String Manipulation | | |-- Stringr Package | | |-- Regular Expressions | |-- Programming Concepts | |-- Apply Family of Functions | | |-- lapply, sapply, tapply, vapply | | | |-- Debugging | | |-- Debugging Tools (browser, debug, trace) | | | |-- Object-Oriented Programming (OOP) | | |-- S3 and S4 Systems | | |-- Reference Classes (R5) | |-- Libraries and Packages | |-- CRAN and Bioconductor | | |-- Installing and Using Packages | | | |-- Popular Packages | | |-- Data Manipulation (dplyr, tidyr) | | |-- Data Visualization (ggplot2, lattice) | | |-- Machine Learning (caret, randomForest) | |-- Reporting and Documentation | |-- RMarkdown | | |-- Creating RMarkdown Documents | | |-- Including Code Chunks | | |-- Generating Reports (HTML, PDF, Word) | |-- Deployment and Reproducibility | |-- Version Control with Git | | |-- Integrating RStudio with GitHub | | | |-- Reproducible Research | | |-- Workflow Practices | | |-- Using renv for Package Management | |-- Working with Big Data | |-- Data.table Package | | |-- Efficient Data Manipulation | | | |-- SparkR | | |-- Using Apache Spark with R | | |-- Handling Large Datasets Free R Programming Courses https://imp.i115008.net/gbJr5r https://bit.ly/33LsOqo https://bit.ly/3shVAJ9 Join @free4unow_backup for more free courses ENJOY LEARNING 👍👍

Python Code to remove Image Background —————————————————————- from rembg import remove from PIL import Image image_path = 'Image Name' ## ---> Change to Image name output_image = 'ImageNew' ## ---> Change to new name your image input = Image.open(image_path) output = remove(input) output.save(output_image)

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Python Project Ideas 👆

Data Science Essential Libraries ✅

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📖 SQL aggregate functions

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5 Python Projects for Beginners 👆

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