I interviewed with Streebo, and the process included questions from OOPs concepts, Machine Learning basics, and simple coding problems such as Fibonacci and factorial implementations. The interview panel seemed focused on testing both fundamental programming knowledge and the ability to apply concepts in real-world scenarios. Questions on Object-Oriented Programming (like inheritance, polymorphism, abstraction, etc.) were straightforward, while Machine Learning questions were more on the theoretical side rather than heavy coding or project-based. The coding part was basic and designed to test logic-building skills rather than advanced problem-solving. Overall, the difficulty level was moderate—a good mix of theory and practice. Pros: Covers fundamentals well. Balanced between coding and concepts. Helpful for candidates with strong basics. Cons: Not many deep-dive or practical ML questions. More focus on theoretical knowledge than hands-on application. Verdict: If you are preparing, focus on core OOPs concepts, ML fundamentals, and basic coding problems. A solid foundation is more valuable here than advanced or niche knowledge.