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)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 👍👍
|
|-- 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 👍👍
❤4
🚀 Full-Stack Developer Roadmap (2025 Edition)
If you want to become a Full-Stack Developer, you need to master both Frontend and Backend development, along with Databases, APIs, DevOps, and Deployment.
Here’s a step-by-step roadmap to guide you:
📌 1. Learn the Fundamentals
Before diving into full-stack development, build a strong foundation.
✅ Internet Basics – How the web works, HTTP/HTTPS, DNS
✅ Basic Git & GitHub – Version control, repositories, branches
✅ Command Line (CLI) – Basic Linux/Terminal commands
📚 Resources:
🔹 GitHub Docs
🔹 HTTP Basics
📌 2. Frontend Development (Building the UI)
The frontend is what users interact with. Learn:
✅ HTML – Structure of webpages
✅ CSS – Styling, Flexbox, Grid, Responsive Design
✅ JavaScript (ES6+) – DOM Manipulation, Async/Await, Fetch API
✅ CSS Frameworks – Bootstrap, Tailwind CSS (optional)
📚 Resources:
🔹 HTML & CSS
🔹 JavaScript (JS.info)
📌 3. Frontend Frameworks (Choose One)
A frontend framework helps in building complex UI faster.
✅ React.js – Most popular, component-based, strong job market
✅ Vue.js – Lightweight, easy to learn, great for small apps
✅ Angular – Powerful but complex, used in large-scale apps
📚 Resources:
🔹 React Docs
🔹 Vue.js Docs
🔹 Angular Docs
📌 4. Backend Development (Server-Side Logic)
The backend handles data processing, authentication, and business logic.
✅ Choose a Backend Language:
JavaScript – Node.js + Express.js
Python – Django / Flask
Java – Spring Boot
PHP, Ruby, Go (Optional)
✅ Backend Fundamentals:
REST APIs (GET, POST, PUT, DELETE)
Authentication (JWT, OAuth, Sessions)
Middleware, Routing, Error Handling
📚 Resources:
🔹 Node.js Docs
🔹 Django Docs
📌 5. Databases & ORM (Data Storage & Management)
Databases store and manage application data. Learn:
✅ SQL Databases – MySQL, PostgreSQL (Structured data)
✅ NoSQL Databases – MongoDB, Firebase (Unstructured data)
✅ ORMs (Object Relational Mapping) – Sequelize (Node.js), SQLAlchemy (Python)
📚 Resources:
🔹 PostgreSQL Guide
🔹 MongoDB Docs
📌 6. Full-Stack Development (Combining Frontend & Backend)
Learn how to connect frontend and backend into a complete web application.
✅ MERN Stack (MongoDB, Express.js, React, Node.js)
✅ MEAN Stack (MongoDB, Express.js, Angular, Node.js)
✅ LAMP Stack (Linux, Apache, MySQL, PHP)
📚 Resources:
🔹 Full-Stack Project Guide
📌 7. Authentication & Security
Web apps must be secure and protected from attacks.
✅ Authentication Methods:
JWT (JSON Web Tokens)
OAuth (Google, Facebook Login)
Session-Based Authentication
✅ Security Best Practices:
Protect against SQL Injection, XSS, CSRF
Hash passwords with bcrypt
Use HTTPS & Helmet.js for secure headers
📚 Resources:
🔹 JWT Guide
🔹 Web Security Best Practices
📌 8. DevOps & Deployment (Hosting Your Projects)
A Full-Stack Developer should know how to deploy applications.
✅ Frontend Deployment:
Netlify, Vercel, GitHub Pages
✅ Backend Deployment:
Heroku, Render, DigitalOcean, AWS, Firebase
✅ CI/CD (Continuous Integration & Deployment):
GitHub Actions, Docker, Jenkins
📚 Resources:
🔹 Deploy Node.js Apps
🔹 AWS Hosting Guide
📌 9. Build Real-World Projects
Apply your knowledge by building full-stack applications.
✅ Beginner Projects:
To-Do List App
Weather App
Personal Portfolio
✅ Intermediate Projects:
Blog CMS (React + Node.js + MongoDB)
E-commerce Website (Product Listing, Cart, Payments)
✅ Advanced Projects:
Social Media App (Posts, Likes, Comments)
Chat App (WebSockets, Real-Time Messaging)
AI-Powered Web App (Chatbot, Image Processing)
📚 Resources:
🔹 Full-Stack Project Ideas
📌 10. Get a Job as a Full-Stack Developer
Once you have projects and skills, start applying for jobs!
✅ Prepare a Strong Resume & Portfolio
✅ Optimize LinkedIn & GitHub Profile
✅ Practice Coding & System Design Interviews
✅ Apply for Jobs (LinkedIn, Indeed, Glassdoor, Wellfound)
📚 Resources:
🔹 LeetCode for Coding Practice
🔹 Interview Prep
Web Development Best Resources
Like for more ❤️
ENJOY LEARNING 👍👍
If you want to become a Full-Stack Developer, you need to master both Frontend and Backend development, along with Databases, APIs, DevOps, and Deployment.
Here’s a step-by-step roadmap to guide you:
📌 1. Learn the Fundamentals
Before diving into full-stack development, build a strong foundation.
✅ Internet Basics – How the web works, HTTP/HTTPS, DNS
✅ Basic Git & GitHub – Version control, repositories, branches
✅ Command Line (CLI) – Basic Linux/Terminal commands
📚 Resources:
🔹 GitHub Docs
🔹 HTTP Basics
📌 2. Frontend Development (Building the UI)
The frontend is what users interact with. Learn:
✅ HTML – Structure of webpages
✅ CSS – Styling, Flexbox, Grid, Responsive Design
✅ JavaScript (ES6+) – DOM Manipulation, Async/Await, Fetch API
✅ CSS Frameworks – Bootstrap, Tailwind CSS (optional)
📚 Resources:
🔹 HTML & CSS
🔹 JavaScript (JS.info)
📌 3. Frontend Frameworks (Choose One)
A frontend framework helps in building complex UI faster.
✅ React.js – Most popular, component-based, strong job market
✅ Vue.js – Lightweight, easy to learn, great for small apps
✅ Angular – Powerful but complex, used in large-scale apps
📚 Resources:
🔹 React Docs
🔹 Vue.js Docs
🔹 Angular Docs
📌 4. Backend Development (Server-Side Logic)
The backend handles data processing, authentication, and business logic.
✅ Choose a Backend Language:
JavaScript – Node.js + Express.js
Python – Django / Flask
Java – Spring Boot
PHP, Ruby, Go (Optional)
✅ Backend Fundamentals:
REST APIs (GET, POST, PUT, DELETE)
Authentication (JWT, OAuth, Sessions)
Middleware, Routing, Error Handling
📚 Resources:
🔹 Node.js Docs
🔹 Django Docs
📌 5. Databases & ORM (Data Storage & Management)
Databases store and manage application data. Learn:
✅ SQL Databases – MySQL, PostgreSQL (Structured data)
✅ NoSQL Databases – MongoDB, Firebase (Unstructured data)
✅ ORMs (Object Relational Mapping) – Sequelize (Node.js), SQLAlchemy (Python)
📚 Resources:
🔹 PostgreSQL Guide
🔹 MongoDB Docs
📌 6. Full-Stack Development (Combining Frontend & Backend)
Learn how to connect frontend and backend into a complete web application.
✅ MERN Stack (MongoDB, Express.js, React, Node.js)
✅ MEAN Stack (MongoDB, Express.js, Angular, Node.js)
✅ LAMP Stack (Linux, Apache, MySQL, PHP)
📚 Resources:
🔹 Full-Stack Project Guide
📌 7. Authentication & Security
Web apps must be secure and protected from attacks.
✅ Authentication Methods:
JWT (JSON Web Tokens)
OAuth (Google, Facebook Login)
Session-Based Authentication
✅ Security Best Practices:
Protect against SQL Injection, XSS, CSRF
Hash passwords with bcrypt
Use HTTPS & Helmet.js for secure headers
📚 Resources:
🔹 JWT Guide
🔹 Web Security Best Practices
📌 8. DevOps & Deployment (Hosting Your Projects)
A Full-Stack Developer should know how to deploy applications.
✅ Frontend Deployment:
Netlify, Vercel, GitHub Pages
✅ Backend Deployment:
Heroku, Render, DigitalOcean, AWS, Firebase
✅ CI/CD (Continuous Integration & Deployment):
GitHub Actions, Docker, Jenkins
📚 Resources:
🔹 Deploy Node.js Apps
🔹 AWS Hosting Guide
📌 9. Build Real-World Projects
Apply your knowledge by building full-stack applications.
✅ Beginner Projects:
To-Do List App
Weather App
Personal Portfolio
✅ Intermediate Projects:
Blog CMS (React + Node.js + MongoDB)
E-commerce Website (Product Listing, Cart, Payments)
✅ Advanced Projects:
Social Media App (Posts, Likes, Comments)
Chat App (WebSockets, Real-Time Messaging)
AI-Powered Web App (Chatbot, Image Processing)
📚 Resources:
🔹 Full-Stack Project Ideas
📌 10. Get a Job as a Full-Stack Developer
Once you have projects and skills, start applying for jobs!
✅ Prepare a Strong Resume & Portfolio
✅ Optimize LinkedIn & GitHub Profile
✅ Practice Coding & System Design Interviews
✅ Apply for Jobs (LinkedIn, Indeed, Glassdoor, Wellfound)
📚 Resources:
🔹 LeetCode for Coding Practice
🔹 Interview Prep
Web Development Best Resources
Like for more ❤️
ENJOY LEARNING 👍👍
❤9
Coding is tricky. Coding in interviews feels even harder. It’s intimidating, uncertain and hard to prepare. Here are 4 ways to do it!
1. Interview Cake: I think it is some of the best prep available and it is targeted toward weaknesses many data scientists have in algorithms and data structures: https://www.interviewcake.com/
2. Leetcode: While developed for software engineering interviews, it has a LOT of useful content for learning algorithms. For data science, I'd suggest focusing on Easy/Medium: https://leetcode.com/
3. Cracking the Coding Interview: Amazing book, sometimes referred to as CTCI. A classic and one you should have: https://cin.ufpe.br/~fbma/Crack/Cracking%20the%20Coding%20Interview%20189%20Programming%20Questions%20and%20Solutions.pdf
4. Daily Coding Problem: The book and the website are awesome. Work on a daily problem. This was my go to resource for when I was looking to stay sharp: https://www.dailycodingproblem.com/
1. Interview Cake: I think it is some of the best prep available and it is targeted toward weaknesses many data scientists have in algorithms and data structures: https://www.interviewcake.com/
2. Leetcode: While developed for software engineering interviews, it has a LOT of useful content for learning algorithms. For data science, I'd suggest focusing on Easy/Medium: https://leetcode.com/
3. Cracking the Coding Interview: Amazing book, sometimes referred to as CTCI. A classic and one you should have: https://cin.ufpe.br/~fbma/Crack/Cracking%20the%20Coding%20Interview%20189%20Programming%20Questions%20and%20Solutions.pdf
4. Daily Coding Problem: The book and the website are awesome. Work on a daily problem. This was my go to resource for when I was looking to stay sharp: https://www.dailycodingproblem.com/
❤4
Many people still aren't fully utilizing the power of Telegram.
There are numerous channels on Telegram that can help you find the latest job and internship opportunities?
Here are some of my top channel recommendations to help you get started 👇👇
Latest Jobs & Internships: https://t.iss.one/getjobss
Jobs Preparation Resources:
https://t.iss.one/jobinterviewsprep
Data Science Jobs:
https://t.iss.one/datasciencej
Interview Tips:
https://t.iss.one/Interview_Jobs
Data Analyst Jobs:
https://t.iss.one/jobs_SQL
AI Jobs:
https://t.iss.one/AIjobz
Remote Jobs:
https://t.iss.one/jobs_us_uk
FAANG Jobs:
https://t.iss.one/FAANGJob
Software Developer Jobs: https://t.iss.one/internshiptojobs
If you found this helpful, don’t forget to like, share, and follow for more resources that can boost your career journey!
Let me know if you know any other useful telegram channel
ENJOY LEARNING👍👍
There are numerous channels on Telegram that can help you find the latest job and internship opportunities?
Here are some of my top channel recommendations to help you get started 👇👇
Latest Jobs & Internships: https://t.iss.one/getjobss
Jobs Preparation Resources:
https://t.iss.one/jobinterviewsprep
Data Science Jobs:
https://t.iss.one/datasciencej
Interview Tips:
https://t.iss.one/Interview_Jobs
Data Analyst Jobs:
https://t.iss.one/jobs_SQL
AI Jobs:
https://t.iss.one/AIjobz
Remote Jobs:
https://t.iss.one/jobs_us_uk
FAANG Jobs:
https://t.iss.one/FAANGJob
Software Developer Jobs: https://t.iss.one/internshiptojobs
If you found this helpful, don’t forget to like, share, and follow for more resources that can boost your career journey!
Let me know if you know any other useful telegram channel
ENJOY LEARNING👍👍
❤4