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This technical problem deals with removing duplicate elements from a linked list. Given an input list with duplicates, the goal is to produce an output list with all duplicates removed. An example input and output is provided.
About this solution: The candidate's solution correctly removes duplicates from a linked list. The approach is straightforward and easy to follow.
This technical problem involves writing a SQL query that returns the names of customers who have placed orders with a total value of more than $100.
About this solution: The solution above is optimal because it uses a JOIN to combine the orders and customers tables. This allows us to access the name column from the customers table.
Write a SQL query to find the second highest salary from the employees table. The table has columns for id and salary. The query should return the salary column.
About this solution: The solution above is optimal because it uses a subquery to find the maximum salary and then uses that value to find the second highest salary.
This problem asks for a SQL query that returns the names and total amounts spent by customers who have made a purchase in the last 30 days.
About this solution: The solution above is optimal because it uses the GROUP BY clause to group the results by customer_id and name, and the SUM() function to calculate the total amount spent by each customer.
Machine Learning / Data Science
DifficultyMedium
This problem is about using machine learning to detect human faces in images. The data set consists of images, and the task is to classify them into two categories: those that contain a human face , and those that do not.
About this solution: The candidate's solution correctly identifies that a machine learning algorithm would be the best solution for this problem. However, the candidate does not provide any details on what type of machine learning algorithm could be used or how it could be trained. Additionally, the candidate does not mention any possible issues that could arise with this approach.
Machine Learning / Data Science
DifficultyMedium
K-means clustering is a simple and effective way to cluster data points into two groups. This method is especially useful when the data set is not linearly separable.
About this solution: The candidate's solution is correct and demonstrates a good understanding of the problem. The candidate has correctly identified that K-means clustering is the best algorithm to use for this problem and has correctly identified that two clusters are required.
The problem asks for a design of a database to store employee information. The input provides an example of the data that would be stored in the database, and the output shows an example of how the data might be organized in a table.
About this solution: The solution is complete and solves the problem. The approach is simple and easy to understand.
The problem asks for a design of a database to store employee information. The input provides an example of the data that would be stored in the database, and the output shows an example of how the data might be organized in a table.
About this solution: This solution is a good start, but it is missing some key information. For example, it does not specify the data types for each column, which is important for database design. Additionally, it does not provide any information on how the table would be used or what kind of data would be stored in it, which would be helpful in determining whether this is the best design for the given purpose.