Coding Interview Resources
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This channel contains the free resources and solution of coding problems which are usually asked in the interviews.

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Typical C++ interview questions sorted by experience

Junior:
- What are the key features of object-oriented programming in C++?
- Explain the differences between public, private, and protected access specifiers in C++.
- Distinguish between function overloading and overriding in C++.
- Compare and contrast abstract classes and interfaces in C++.
- Can an interface inherit from another interface in C++?
- Define the static keyword in C++ and its significance.
- Is it possible to override a static method in C++?
- Explain the concepts of polymorphism and inheritance in C++.
- Can constructors be inherited in C++?
- Discuss pass-by-reference and pass-by-value for objects in C++.
- Compare == and .equals for string comparison in C++.
- Explain the purposes of the hashCode() and equals() functions.
- What does the Serializable interface do? How is it related to Parcelable in Android?
- Differentiate between Array and ArrayList in C++. When would you use each?
- Explain the distinction between Integer and int in C++.
- Define ThreadPool and discuss its advantages over using simple threads.
- Differentiate between local, instance, and class variables in C++.

Mid:
- What is reflection in C++?
- Define dependency injection and name a few libraries. Have you used any?
- Explain strong, soft, and weak references in C++.
- Interpret the meaning of the synchronized keyword.
- Can memory leaks occur in C++?
- Is it necessary to set references to null in C++?
- Why is a String considered immutable?
- Discuss transient and volatile modifiers in C++.
- What is the purpose of the finalize() method?
- How does the try{} finally{} block work in C++?
- Explain the difference between object instantiation and initialization.
- Under what conditions is a static block executed in C++?
- Why are generics used in C++?
- Mention some design patterns you are familiar with. Which do you typically use?
- Name some types of testing methodologies in C++.

Senior:
- Explain how std::stoi (string to integer) works in C++.
- What is the "double-check locking" problem, and how can it be solved in C++?
- Differentiate between StringBuffer and StringBuilder in C++.
- How is StringBuilder implemented to avoid the immutable string allocation problem?
- Explain the purpose of the Class.forName method in C++.
- Define Autoboxing and Unboxing in C++.
- What's the difference between Enumeration and Iterator in C++?
- Explain the difference between fail-fast and fail-safe in C++.
- What is PermGen in C++?
- Describe a Java priority queue.
- How is performance influenced by using the same number in different types: Int, Double, and Float?
- Explain the concept of the Java Heap.
- What is a daemon thread?
- Can a dead thread be restarted in C++?

โœ… Best Telegram channels to get free coding & data science resources
-> https://t.me/addlist/4q2PYC0pH_VjZDk5

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Learning CSS in 30 days๐Ÿ‘‡

Day 1-5: Introduction to CSSโšก

Learn the basics of HTML (if you don't know already)
Understand what CSS is and how it is used to style web pages
Learn how to add CSS to an HTML page
Understand the different ways to add CSS to an HTML page (inline, internal, external)
Learn about selectors and how they are used to target HTML elements

Day 6-10: Box model and layout๐ŸŽ

Understand the box model and how it affects the layout of HTML elements
Learn how to manipulate the box model using padding, margin, and border
Learn how to position elements using CSS (relative, absolute, fixed, static, sticky)
Understand the different display properties (block, inline, inline-block) and how they affect layout
Learn how to create responsive layouts using media queries

Day 11-15: Typography and colors โค๏ธโ€๐Ÿ”ฅ

Understand the CSS font properties (font-family, font-size, font-weight, etc.)
Learn how to style text using CSS (color, text-decoration, text-align, etc.)
Understand the CSS color property and how to use it to set colors
Learn about gradients, transparency, and opacity
Understand how to use CSS to create hover and active effects

Day 16-20: Advanced CSS concepts๐Ÿ‘ฉโ€๐Ÿ’ป

Learn about CSS preprocessors like Sass and Less
Understand how to use CSS frameworks like Bootstrap and Foundation
Learn about CSS animations and transitions
Understand how to use flexbox for layout
Learn how to use CSS grid for layout

Day 21-25: CSS best practices and optimization๐Ÿ’ฅ

Learn about CSS code organization and best practices
Understand how to optimize CSS for performance
Learn how to use CSS vendor prefixes for cross-browser compatibility
Understand how to debug CSS using browser developer tools
Learn how to use CSS linting tools to catch errors

Day 26-30: Practice and projects๐Ÿ‘ฉโ€๐Ÿซ

Create simple projects to practice what you've learned
Work on more complex projects to challenge yourself
Join CSS communities to learn from others and get feedback on your work
Read articles and tutorials to stay up-to-date with the latest CSS trends and techniques

Reflect on what you've learned and identify areas for improvement
Remember, this is just a roadmap, and you can adjust it based on your learning style and pace.

The most important thing is to stay consistent and practice regularly. Good luck!

Web Development Best Resources: https://topmate.io/coding/930165

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If you want to get a job as a machine learning engineer, donโ€™t start by diving into the hottest libraries like PyTorch,TensorFlow, Langchain, etc.

Yes, you might hear a lot about them or some other trending technology of the year...but guess what!

Technologies evolve rapidly, especially in the age of AI, but core concepts are always seen as more valuable than expertise in any particular tool. Stop trying to perform a brain surgery without knowing anything about human anatomy.

Instead, here are basic skills that will get you further than mastering any framework:


๐Œ๐š๐ญ๐ก๐ž๐ฆ๐š๐ญ๐ข๐œ๐ฌ ๐š๐ง๐ ๐’๐ญ๐š๐ญ๐ข๐ฌ๐ญ๐ข๐œ๐ฌ - My first exposure to probability and statistics was in college, and it felt abstract at the time, but these concepts are the backbone of ML.

You can start here: Khan Academy Statistics and Probability - https://www.khanacademy.org/math/statistics-probability

๐‹๐ข๐ง๐ž๐š๐ซ ๐€๐ฅ๐ ๐ž๐›๐ซ๐š ๐š๐ง๐ ๐‚๐š๐ฅ๐œ๐ฎ๐ฅ๐ฎ๐ฌ - Concepts like matrices, vectors, eigenvalues, and derivatives are fundamental to understanding how ml algorithms work. These are used in everything from simple regression to deep learning.

๐๐ซ๐จ๐ ๐ซ๐š๐ฆ๐ฆ๐ข๐ง๐  - Should you learn Python, Rust, R, Julia, JavaScript, etc.? The best advice is to pick the language that is most frequently used for the type of work you want to do. I started with Python due to its simplicity and extensive library support, and it remains my go-to language for machine learning tasks.

You can start here: Automate the Boring Stuff with Python - https://automatetheboringstuff.com/

๐€๐ฅ๐ ๐จ๐ซ๐ข๐ญ๐ก๐ฆ ๐”๐ง๐๐ž๐ซ๐ฌ๐ญ๐š๐ง๐๐ข๐ง๐  - Understand the fundamental algorithms before jumping to deep learning. This includes linear regression, decision trees, SVMs, and clustering algorithms.

๐ƒ๐ž๐ฉ๐ฅ๐จ๐ฒ๐ฆ๐ž๐ง๐ญ ๐š๐ง๐ ๐๐ซ๐จ๐๐ฎ๐œ๐ญ๐ข๐จ๐ง:
Knowing how to take a model from development to production is invaluable. This includes understanding APIs, model optimization, and monitoring. Tools like Docker and Flask are often used in this process.

๐‚๐ฅ๐จ๐ฎ๐ ๐‚๐จ๐ฆ๐ฉ๐ฎ๐ญ๐ข๐ง๐  ๐š๐ง๐ ๐๐ข๐  ๐ƒ๐š๐ญ๐š:
Familiarity with cloud platforms (AWS, Google Cloud, Azure) and big data tools (Spark) is increasingly important as datasets grow larger. These skills help you manage and process large-scale data efficiently.

You can start here: Google Cloud Machine Learning - https://cloud.google.com/learn/training/machinelearning-ai

I love frameworks and libraries, and they can make anyone's job easier.

But the more solid your foundation, the easier it will be to pick up any new technologies and actually validate whether they solve your problems.

Best Data Science & Machine Learning Resources: https://topmate.io/coding/914624

All the best ๐Ÿ‘๐Ÿ‘
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Important Interview Questions with Answers ๐Ÿ’ปโœ…
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List of topics you need to cover if you're preparing for Java Interviews based on current Job market:

1. Core Java Fundamentals (Refer to already posted topics)
2. Advanced Java
- Design Patterns
- Multithreading
- Java Memory Model
- Performance Optimization
- Reflection & Dynamic Proxies
3. Spring Framework
- Spring core concepts
- Spring boot
- Spring Data JPA
- Spring Security
- Spring cloud
- Spring webflux
4. Hibernate
5. Testing (JUnit, Mockito, Integration, Functional, Performance Testing)
6. Build Tools (Maven / Gradle)
7. Logging
8. RDBMS, NoSQL DBs
9. WebSecurity Concepts
10. REST API concepts
11. CI/CD (Jenkins, GitHub Actions)
12. Containerization (Docker, Kubernetes)
13. Version Control (GitHub)
14. Monitoring (Grafana, ELK Stack etc)
15. Cloud (AWS, Azure, GCP (Very rare) )
16. Spring boot microservices
16. Messaging systems
17. Caching Strategies
18. System Design
19. Data Structures
20. Algorithms
21. Agile Methodologies
22. Behavioral questions
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what programming language do you use most often ๐ŸŒŸ
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๐Ÿ”Ÿ Web development project ideas for beginners

Personal Portfolio Website: Create a website showcasing your skills, projects, and resume. This will help you practice HTML, CSS, and potentially some JavaScript for interactivity.

To-Do List App: Build a simple to-do list application using HTML, CSS, and JavaScript. You can gradually enhance it by adding features like task priority, due dates, and local storage.

Blog Platform: Create a basic blog platform where users can create, edit, and delete posts. This will give you experience with user authentication, databases, and CRUD operations.

E-commerce Website: Design a mock e-commerce site to learn about product listings, shopping carts, and checkout processes. This project will introduce you to handling user input and creating dynamic content.

Weather App: Develop a weather app that fetches data from a weather API and displays current conditions and forecasts. This project will involve API integration and working with JSON data.

Recipe Sharing Site: Build a platform where users can share and browse recipes. You can implement search functionality and user authentication to enhance the project.

Social Media Dashboard: Create a simplified social media dashboard that displays metrics like followers, likes, and comments. This project will help you practice data visualization and working with APIs.

Online Quiz App: Develop an online quiz application that lets users take quizzes on various topics. You can include features like multiple-choice questions, timers, and score tracking.

Personal Blog: Start your own blog by developing a content management system (CMS) where you can create, edit, and publish articles. This will give you hands-on experience with database management.

Event Countdown Timer: Build a countdown timer for upcoming events. You can make it interactive by allowing users to set their own event names and dates.

Remember, the key is to start small and gradually add complexity to your projects as you become more comfortable with different technologies concepts. These projects will not only showcase your skills to potential employers but also help you learn and grow as a web developer.

Free Resources to learn web development https://t.me/free4unow_backup/554

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Top 10 Web Development Technologies ๐ŸŒ

1. ๐ŸŸจ JavaScript โ€” 98% usage

2. ๐Ÿ”ต TypeScript โ€” 78% adoption

3. ๐ŸŸข Node.js โ€” 75% backend choice

4. โš›๏ธ React โ€” 70% frontend framework

5. ๐Ÿ…ฐ๏ธ Angular โ€” 55% enterprise use

6. ๐Ÿ’š Vue.js โ€” 49% growing popularity

7. ๐Ÿ Python โ€” 48% for full-stack

8. ๐Ÿ’Ž Ruby on Rails โ€” 45% rapid development

9. ๐Ÿ˜ PHP โ€” 43% widespread use

10. โ˜• Java โ€” 40% enterprise solutions
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11. ๐Ÿฆ€ Rust โ€” 38% performance-critical apps

12. ๐ŸŽฏ Dart โ€” 35% with Flutter for web

13. ๐Ÿ”ท GraphQL โ€” 33% API queries

14. ๐Ÿƒ MongoDB โ€” 30% NoSQL database

15. ๐Ÿณ Docker โ€” 28% containerization

16. โ˜๏ธ AWS โ€” 25% cloud services

17. ๐Ÿ”ถ Svelte โ€” 22% compile-time framework

18. ๐Ÿ”ท Next.js โ€” 20% React framework

19. ๐ŸŸฃ Blazor โ€” 18% .NET web apps

20. ๐ŸŸข Deno โ€” 15% secure runtime
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All 25 Algorithms...
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Interview QnAs For ML Engineer

1.What are the various steps involved in an data analytics project?

The steps involved in a data analytics project are:

Data collection
Data cleansing
Data pre-processing
EDA
Creation of train test and validation sets
Model creation
Hyperparameter tuning
Model deployment


2. Explain Star Schema.

Star schema is a data warehousing concept in which all schema is connected to a central schema.


3. What is root cause analysis?

Root cause analysis is the process of tracing back of occurrence of an event and the factors which lead to it. Itโ€™s generally done when a software malfunctions. In data science, root cause analysis helps businesses understand the semantics behind certain outcomes.


4. Define Confounding Variables.

A confounding variable is an external influence in an experiment. In simple words, these variables change the effect of a dependent and independent variable. A variable should satisfy below conditions to be a confounding variable :

Variables should be correlated to the independent variable.
Variables should be informally related to the dependent variable.
For example, if you are studying whether a lack of exercise has an effect on weight gain, then the lack of exercise is an independent variable and weight gain is a dependent variable. A confounder variable can be any other factor that has an effect on weight gain. Amount of food consumed, weather conditions etc. can be a confounding variable.

Data Science & Machine Learning Resources: https://whatsapp.com/channel/0029Va8v3eo1NCrQfGMseL2D

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How to master Python from scratch๐Ÿš€

1. Setup and Basics ๐Ÿ
   - Install Python ๐Ÿ–ฅ๏ธ: Download Python and set it up.
   - Hello, World! ๐ŸŒ: Write your first Hello World program.

2. Basic Syntax ๐Ÿ“œ
   - Variables and Data Types ๐Ÿ“Š: Learn about strings, integers, floats, and booleans.
   - Control Structures ๐Ÿ”„: Understand if-else statements, for loops, and while loops.
   - Functions ๐Ÿ› ๏ธ: Write reusable blocks of code.

3. Data Structures ๐Ÿ“‚
   - Lists ๐Ÿ“‹: Manage collections of items.
   - Dictionaries ๐Ÿ“–: Store key-value pairs.
   - Tuples ๐Ÿ“ฆ: Work with immutable sequences.
   - Sets ๐Ÿ”ข: Handle collections of unique items.

4. Modules and Packages ๐Ÿ“ฆ
   - Standard Library ๐Ÿ“š: Explore built-in modules.
   - Third-Party Packages ๐ŸŒ: Install and use packages with pip.

5. File Handling ๐Ÿ“
   - Read and Write Files ๐Ÿ“
   - CSV and JSON ๐Ÿ“‘

6. Object-Oriented Programming ๐Ÿงฉ
   - Classes and Objects ๐Ÿ›๏ธ
   - Inheritance and Polymorphism ๐Ÿ‘จโ€๐Ÿ‘ฉโ€๐Ÿ‘ง

7. Web Development ๐ŸŒ
   - Flask ๐Ÿผ: Start with a micro web framework.
   - Django ๐Ÿฆ„: Dive into a full-fledged web framework.

8. Data Science and Machine Learning ๐Ÿง 
   - NumPy ๐Ÿ“Š: Numerical operations.
   - Pandas ๐Ÿผ: Data manipulation and analysis.
   - Matplotlib ๐Ÿ“ˆ and Seaborn ๐Ÿ“Š: Data visualization.
   - Scikit-learn ๐Ÿค–: Machine learning.

9. Automation and Scripting ๐Ÿค–
   - Automate Tasks ๐Ÿ› ๏ธ: Use Python to automate repetitive tasks.
   - APIs ๐ŸŒ: Interact with web services.

10. Testing and Debugging ๐Ÿž
    - Unit Testing ๐Ÿงช: Write tests for your code.
    - Debugging ๐Ÿ”: Learn to debug efficiently.

11. Advanced Topics ๐Ÿš€
    - Concurrency and Parallelism ๐Ÿ•’
    - Decorators ๐ŸŒ€ and Generators โš™๏ธ
    - Web Scraping ๐Ÿ•ธ๏ธ: Extract data from websites using BeautifulSoup and Scrapy.

12. Practice Projects ๐Ÿ’ก
    - Calculator ๐Ÿงฎ
    - To-Do List App ๐Ÿ“‹
    - Weather App โ˜€๏ธ
    - Personal Blog ๐Ÿ“

13. Community and Collaboration ๐Ÿค
    - Contribute to Open Source ๐ŸŒ
    - Join Coding Communities ๐Ÿ’ฌ
    - Participate in Hackathons ๐Ÿ†

14. Keep Learning and Improving ๐Ÿ“ˆ
    - Read Books ๐Ÿ“–: Like "Automate the Boring Stuff with Python".
    - Watch Tutorials ๐ŸŽฅ: Follow video courses and tutorials.
    - Solve Challenges ๐Ÿงฉ: On platforms like LeetCode, HackerRank, and CodeWars.

15. Teach and Share Knowledge ๐Ÿ“ข
    - Write Blogs โœ๏ธ
    - Create Video Tutorials ๐Ÿ“น
    - Mentor Others ๐Ÿ‘จโ€๐Ÿซ

I have curated the best interview resources to crack Python Interviews ๐Ÿ‘‡๐Ÿ‘‡
https://topmate.io/coding/898340

Hope you'll like it

Like this post if you need more resources like this ๐Ÿ‘โค๏ธ
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Types of Data Structures ๐Ÿ‘†
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