Coding Interview Resources

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11. 🦀 Rust — 38% performance-critical apps 12. 🎯 Dart — 35% with Flutter for web 13. 🔷 GraphQL — 33% API queries 14. 🍃 MongoDB — 30% NoSQL database 15. 🐳 Docker — 28% containerization 16. ☁️ AWS — 25% cloud services 17. 🔶 Svelte — 22% compile-time framework 18. 🔷 Next.js — 20% React framework 19. 🟣 Blazor — 18% .NET web apps 20. 🟢 Deno — 15% secure runtime

Top 10 Web Development Technologies 🌐 1. 🟨 JavaScript — 98% usage 2. 🔵 TypeScript — 78% adoption 3. 🟢 Node.js — 75% backend choice 4. ⚛️ React — 70% frontend framework 5. 🅰️ Angular — 55% enterprise use 6. 💚 Vue.js — 49% growing popularity 7. 🐍 Python — 48% for full-stack 8. 💎 Ruby on Rails — 45% rapid development 9. 🐘 PHP — 43% widespread use 10. ☕ Java — 40% enterprise solutions

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what programming language do you use most often 🌟

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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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Important Interview Questions with Answers 💻✅

𝗧𝗼𝗽 𝟱 𝗪𝗲𝗯𝘀𝗶𝘁𝗲𝘀 𝘁𝗼 𝗟𝗲𝗮𝗿𝗻 𝗝𝗮𝘃𝗮𝗦𝗰𝗿𝗶𝗽𝘁 𝗶𝗻 𝟮𝟬𝟮𝟱😍 Learning JavaScript doesn’t have to be boring anymore!💫 If endless tutorials make your eyes glaze over, we’ve got just the thing — these super fun & interactive platforms turn learning JavaScript into a game👨‍💻 𝐋𝐢𝐧𝐤👇:- https://pdlink.in/3T4yYbP Perfect for daily practice, weekend sprints, or anyone who learns better with hands-on interaction!9✅️

If you want to get a job as a machine learning engineer, don’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: 𝐌𝐚𝐭𝐡𝐞𝐦𝐚𝐭𝐢𝐜𝐬 𝐚𝐧𝐝 𝐒𝐭𝐚𝐭𝐢𝐬𝐭𝐢𝐜𝐬 - 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 𝐋𝐢𝐧𝐞𝐚𝐫 𝐀𝐥𝐠𝐞𝐛𝐫𝐚 𝐚𝐧𝐝 𝐂𝐚𝐥𝐜𝐮𝐥𝐮𝐬 - 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. 𝐏𝐫𝐨𝐠𝐫𝐚𝐦𝐦𝐢𝐧𝐠 - 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/ 𝐀𝐥𝐠𝐨𝐫𝐢𝐭𝐡𝐦 𝐔𝐧𝐝𝐞𝐫𝐬𝐭𝐚𝐧𝐝𝐢𝐧𝐠 - Understand the fundamental algorithms before jumping to deep learning. This includes linear regression, decision trees, SVMs, and clustering algorithms. 𝐃𝐞𝐩𝐥𝐨𝐲𝐦𝐞𝐧𝐭 𝐚𝐧𝐝 𝐏𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧: 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. 𝐂𝐥𝐨𝐮𝐝 𝐂𝐨𝐦𝐩𝐮𝐭𝐢𝐧𝐠 𝐚𝐧𝐝 𝐁𝐢𝐠 𝐃𝐚𝐭𝐚: 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 👍👍

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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++? ✅ Best Telegram channels to get free coding & data science resources -> https://t.me/addlist/4q2PYC0pH_VjZDk5 ENJOY LEARNING 👍👍

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