What is a p-value and how to draw conclusions from it when analyzing an A/B test (rejecting or not rejecting the null hypothesis)?
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Data Analyst
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Explain the algorithm for computing the dot product of two compressed (RLE-encoded) vectors in a single pass without unpacking them. What is the asymptotic time complexity?
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Has ML been used for feature selection in a car classification task?
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Tell us about your most interesting projects and why you want to develop in analytics
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D. Valera and vending machines In a business center, there are 10 externally identical vending machines with chocolates. Each machine dispenses a chocolate with its own fixed probability, which is initially unknown and may differ between machines. Sweet-tooth Valera wants to get as many chocolates as possible, but his budget is limited to 200 tugrik. Each purchase attempt (using any machine once) costs exactly 1 tugrik — payment is made regardless of whether the machine dispenses a chocolate or not. Valera, trying to learn the probabilities of the machines, met security guard Alexei, who shared an important piece of information. The guard told him that 2/5 of the machines have probabilities drawn from a uniform distribution on [0.2, 0.3], 2/5 from [0.4, 0.5], and the rest from [0.85, 1]. Your task is to devise an algorithm that helps Valera get as many chocolates as possible. Interaction protocol This is an interactive task. Your program should first output the number of the machine — a number from 0 to 9. Then the system (interactor) will return the result: 1 if a chocolate was dispensed, or 0 if not. Your program can read this value (for example, via input()) to use in further calculations. Scoring system In each test, the percentage of successful attempts to get chocolates will be evaluated. If this percentage exceeds 75%, the test is considered passed. Note It is recommended to use Python 3.8 (Handbook DS) as the compiler.
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Would the proposed solution work for SQLite?
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Once, a Yandex Ads anti-fraud intern joined the team. While the fraudster group was active, which simulated traffic on their sites through bot visits, and thus received money for ad impressions by bots, the intern's task was to find all such fraudulent sites with fake traffic. Interestingly, all traffic on these sites was generated with IP substitution, making it seem as if a bot was visiting from city A, but in reality, the device was in a completely different location. A lot of time passed, and the intern tried to cover this entire fraud group, even managing to catch some sites in parts. But the whole network could not be caught. After some time, he noticed a news report: in city A, on 02.08.2025, mobile internet was completely absent. However, wired (home) internet continued to work. Given this, how can the intern find all fake sites? You have logs of sites in a table format for the period from 30.07.2025 to 10.08.2025: timestamp | site_id | city_id Each record corresponds to a visit to a site by one device. It is known that bot traffic changes significantly less than real traffic per day. Your task is to find all sites whose traffic was mainly composed of bots that faked their region to city A. Note The table containing the data is called logs. Example of a table record: timestamp | site_id | city_id [phone]:13:53 | 6e84d9b71ca44aea | A
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What is the asymptotic complexity of the proposed solution in terms of time and memory?
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Why does standardizing the answer format in a benchmark still make sense, even if it limits the model?
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Can the Product of Array Except Self problem be solved more simply if any operations are allowed?
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-- 1.2 How will the answer change if you switch the JOIN type to LEFT? -- 1.3 Specify the order of execution of the operators in this query. from join group by select order by limit -- 2. The campaigns table has been fixed: duplicates removed, primary key added. -- More campaigns were conducted, and due to bugs, users started receiving failed communication delivery attempts, and some couldn't see it at all. -- For the promotional campaigns sent to users: -- 2.1 Write a query that outputs the number of users who successfully received communication for each campaign. -- 2.2 Modify the query to output: the number of users who ultimately did not receive any successful communication, for each campaign?
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What is the memory complexity of the Product of Array Except Self problem and what additional variables are used?
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How to compare the model's answer with the ground truth in a benchmark? What metric to use?
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A. The Best Scientific Laboratory In a certain city, several scientific laboratories are researching bacterial cultures. They study a sequence of samples, where each sample belongs to a specific strain (type of bacteria). The chief biological research university announced a contest: to find the maximum number of consecutive samples that can be analyzed considering the restriction. Specifically: in any continuous segment of the sequence, there should be no more than K different strains. Our laboratory strives to become the best in the city. To win the contest, we need to find exactly such a maximum length of a segment that satisfies the strict condition. We are counting on you, because in case of victory, the laboratory will receive a grant that will open new horizons for our research. Input format The first line contains two numbers: N — the length of the sample sequence and K — the restriction on the number of different strains. The second line contains N numbers — the elements of the sequence. Output format The program should output the number of the maximum length of a segment of the sample sequence. Example 1 Input [phone] Output 3
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Return a list of the same size for a list of integers, where at the i-th position – the product of all elements of the list except the element at position i of the original list. Examples: [2, 3, 4] -> [3*4, 2*4, 2*3] -> [12, 8, 6] def product_except_self(nums: list[int]) -> list[int]: # your code here
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Tell us about the stack and tools you have used and mastered.
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Write a complete sum_series function in Python and test it with an example from the task.
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How interested are you in machine learning and would you like to apply it as a tool in your work?
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How would you create a geometry benchmark? Describe the chain from idea to final dataset.
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What will change if you replace COUNT(*) with COUNT() without an argument?
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