Machine Learning / AI
What loss function did you use when fine-tuning the embedder?
What was actually more difficult than initially expected?
How did you choose the model for embeddings? Were there document filtering and reranking stages?
Are you familiar with GigaChat? Do you have experience working with it?
How do you combine studying and working in parallel?
Tell us about yourself and your experience as a systems analyst
What is linear regression and what are the options for its solution?
What is tokenization?
What does the speed model translate into a class label?
Was the toolcalling native or through prompt (parsing)?
What is dropout and how does it work during training and inference?
-- # -- Marketers launch promo campaigns in the app. There are two tables: -- # -- campaigns - list of campaigns -- # -- - campaign - campaign name -- # -- - action_type - campaign type: "push" or "banner" -- # -- communications - backend log of sending communications of these campaigns to users -- # -- - user_id - user identifier -- # -- - campaign - campaign name -- # -- - status - event status: "success" or "error" -- ------------------------------------------------------------------------------------------------------------------------ -- # -- 1. Initially, the campaigns table has 4 rows: -- # -- | campaign | action_type | -- # -- |-------------|-------------| -- # -- | promo_dogs | push | -- # -- | promo_cats | banner | <- randomly duplicated -- # -- | promo_cats | banner | <- two rows -- # -- | promo_rats | push | # # -- Also known that: -- # -- campaigns promo_dogs and promo_cats were successfully conducted on 100 users each, and each user received one communication, -- # -- while promo_rats is only planned. -- # -- 1.1 What will the query output: SELECT campaign, COUNT(*) as rows, COUNT(DISTINCT co.user_id) AS users FROM campaigns AS ca INNER JOIN communications AS co ON ca.campaign = co.campaign GROUP BY ca.campaign AS campaign -- # -- 1.2 How will the answer change if you change the JOIN type to LEFT? -- # -- 1.3 List the order of execution of the operators in this query. -- Answer: promo_dogs ... ...
What hyperparameters of LoRA do you know?
Tell us about yourself and your work experience.
Do you have experience passing interviews with AI?
Where is the prompt stored and how is it displayed in the monitoring system?
In terms of speed, which is faster — a regular agent with tools or a multi-agent system?
Have you had experience working in fully English-speaking teams?
How was reporting to the team lead of the multi-agent system carried out?
Tell me about LoRA: what is it, and why is it needed?