Awful questions about algorithms (not ml) and data structures, no sense in these type of questions. And awful tasks like old fashioned brainteasers. Not suitable for ML position. Only negative impression
Candidatei-me online. Fiz uma entrevista na empresa Yandex.
Entrevista
I recently interviewed for a Middle Machine Learning Engineer position at Yandex.
Overall, the experience was insightful and challenging, providing a good sense of the company's technical depth and expectations.
I got easy task from leetcode: 680. Valid Palindrome II
Candidatei-me por meio de recrutador(a). O processo levou 3 meses. Fui entrevistado pela Yandex (Moscovo, ) em jan. de 2022
Entrevista
I recently had the opportunity to interview for a Machine Learning Engineer (MLE) position at Yandex Moscow, and I must say that the entire experience was exceptional. The MLE interview process at Yandex Moscow not only demonstrated the company's commitment to technical excellence but also reflected their dedication to fostering a positive and collaborative environment for candidates.
Perguntas de entrevista [1]
Pergunta 1
- Explain the concept of overfitting in machine learning and describe techniques to mitigate it. - How would you approach feature selection and feature engineering for a given machine learning task? Provide examples of relevant features for a sentiment analysis problem. - Discuss the differences between supervised learning and unsupervised learning algorithms. When would you choose one over the other for a given problem? - Describe the working principles of convolutional neural networks (CNNs) and their applications in computer vision tasks. How do they handle spatial hierarchies and achieve translation invariance? - Suppose you are given a dataset with imbalanced classes for a binary classification problem. How would you address this issue and improve the performance of the model? Explain different techniques you can use, such as oversampling, undersampling, or cost-sensitive learning.
