Young, energetic, flat management, afternoon tea.
Hard to get promoted, long working hours.
Machine learning knowledge and code. - LeetCode (medium, hard with Python) - AUC definition - Methods for dealing with long-tailed data - Causal inference - Machine learning questions - Deep learning methods such as attention mechanisms
Interview 1: Self-introduction -- bias-variance trade-off, how to avoid overfitting/underfitting -- coding. Interview 2: Talk about research: how to find the closest vector to a given vector in N given vectors? How to approximate this when N is ve
Two coding questions were presented. One was categorized as easy, and the other as medium (though I believe it should have been categorized as hard). The topic was finding a node at a k distance in a binary tree. The interviewer provided practical
Machine learning knowledge and code. - LeetCode (medium, hard with Python) - AUC definition - Methods for dealing with long-tailed data - Causal inference - Machine learning questions - Deep learning methods such as attention mechanisms
Interview 1: Self-introduction -- bias-variance trade-off, how to avoid overfitting/underfitting -- coding. Interview 2: Talk about research: how to find the closest vector to a given vector in N given vectors? How to approximate this when N is ve
Two coding questions were presented. One was categorized as easy, and the other as medium (though I believe it should have been categorized as hard). The topic was finding a node at a k distance in a binary tree. The interviewer provided practical