Post by account_disabled on Mar 11, 2024 5:03:39 GMT
It shows whether they could handle concurrency in programming implementations that deal with large volumes of data. 20. Is it possible to cut two strings, A and B, that are the same length at a common point so that the first section of A and the second section of B create a palindrome? Although this is a software engineering question, it is useful to check whether candidates have knowledge of data structures and algorithms. There are several routes to check for palindromes. 21. Explain how you would implement a recommendation system for our company's clients. This is an opportunity for your candidates to show that they have researched your company and your industry. A good candidate would demonstrate that they understand what generates revenue for your company and the types of customers your business has. And he would explain how he could implement machine learning models to solve your company's problems. 22. Where do you usually get data sets from? This is another question to check if your candidate is really interested in machine learning. Someone who really loves machine learning has probably created their own side projects and therefore knows where to get great data sets.
This type of question helps you separate the passionate engineers from the engineers who only work for a salary. 23. Have you trained models for fun? What hardware or graphics processing units did you use? This Bahamas Mobile Number List question helps you find candidates who have done machine learning projects in their spare time, not just corporate jobs. Test whether your candidates can allocate GPU time effectively and know how to source resources for projects. 24. How would you approach the "Netflix Prize" contest? Qualified candidates will be introduced to the Netflix Prize, a contest in which Netflix offered a $1 million prize to whoever could create the best collaborative filtering algorithm. BellKor the winners used several different methods to improve the algorithm by 10%. Strong candidates will remember not only the contest, but also the solution BellKor created, demonstrating that they have been passionate about machine learning for a long time. 25. Explain how primary and foreign keys are related in SQL.
Machine learning engineers must master many key data formats, including SQL. The answers to this question will show whether your candidate can manipulate SQL databases. Candidates should explain that they can match and join tables using foreign keys and the primary key of the corresponding table. They should also explain to you how they would configure SQL tables. 26. Have you used Spark or other big data tools? park is the most requested big data tool. However, if your company uses a different tool, feel free to mention it instead of Spark. This question will help you identify candidates who are familiar with these tools and are able to get to work. The answers will also show you who has spent time researching and familiarizing themselves with your company before the interview. 27. When do you think ensemble techniques could be practical? In this case, you are evaluating your candidate's ability to increase predictive power. Ensemble techniques combine different learning algorithms to create improved predictive performance. This approach creates a robust model that is typically resilient to small changes in the data that could bias the prediction accuracy.
This type of question helps you separate the passionate engineers from the engineers who only work for a salary. 23. Have you trained models for fun? What hardware or graphics processing units did you use? This Bahamas Mobile Number List question helps you find candidates who have done machine learning projects in their spare time, not just corporate jobs. Test whether your candidates can allocate GPU time effectively and know how to source resources for projects. 24. How would you approach the "Netflix Prize" contest? Qualified candidates will be introduced to the Netflix Prize, a contest in which Netflix offered a $1 million prize to whoever could create the best collaborative filtering algorithm. BellKor the winners used several different methods to improve the algorithm by 10%. Strong candidates will remember not only the contest, but also the solution BellKor created, demonstrating that they have been passionate about machine learning for a long time. 25. Explain how primary and foreign keys are related in SQL.
Machine learning engineers must master many key data formats, including SQL. The answers to this question will show whether your candidate can manipulate SQL databases. Candidates should explain that they can match and join tables using foreign keys and the primary key of the corresponding table. They should also explain to you how they would configure SQL tables. 26. Have you used Spark or other big data tools? park is the most requested big data tool. However, if your company uses a different tool, feel free to mention it instead of Spark. This question will help you identify candidates who are familiar with these tools and are able to get to work. The answers will also show you who has spent time researching and familiarizing themselves with your company before the interview. 27. When do you think ensemble techniques could be practical? In this case, you are evaluating your candidate's ability to increase predictive power. Ensemble techniques combine different learning algorithms to create improved predictive performance. This approach creates a robust model that is typically resilient to small changes in the data that could bias the prediction accuracy.