Perguntas de entrevista da empresa PakWheels

There are 2 interview rounds I cleared the first one but second interview was taken by Engineering head Salman Haider. He literally has some attitude issues and a fragile ego. I gave him 2 solutions for the given problem but he wanted the solution which is in his mind. Also he is clingy and leech type of person he just want to let you down like he showing you that he knows better than you and that is fine but why you showing off? (May b this is the reason he is in same company for 10 years). He gave me a whole feature of Pakwheels app to implement in last 10 minutes even he can't do that himself within same time bro i needed 5-8mins to just read and process that in my mind then he told me to give him an overview of it and i gave the right approach but he told me this does not looks correct and ask me to see this after interview and he disconnected. I confirmed my solution afterwards it was correct.

The interview process consisted of three stages, with two rounds conducted online and one round being an onsite interview. Throughout the interview process, I was assessed on various aspects of machine learning (ML) and deep learning (DL). During the online interviews, I was asked a series of technical questions related to ML and DL. These questions covered topics such as: Fundamentals of machine learning algorithms, including supervised and unsupervised learning. Popular deep learning architectures like convolutional neural networks (CNNs), recurrent neural networks (RNNs), and transformer models. Evaluation metrics used in ML/DL, such as accuracy, precision, recall, F1 score, etc. Techniques for handling overfitting and underfitting in machine learning models. Feature engineering and data preprocessing techniques. Additionally, the interviewers asked me to explain real-world use cases of ML and DL in various domains like computer vision, natural language processing, and speech recognition. In the onsite interview, I had the opportunity to showcase my practical skills by working on coding exercises and solving ML/DL problems on a whiteboard or using a computer. This stage of the interview allowed me to demonstrate my ability to apply theoretical concepts to practical scenarios and show my problem-solving skills. Throughout the process, the interviewers evaluated not only my technical knowledge but also my ability to communicate effectively, think critically, and approach complex problems. It was a comprehensive evaluation of my ML and DL expertise as well as my overall suitability for the role.