Statistics reveal that 70% of candidates preparing for machine learning interviews struggle with the depth of algorithmic details. A recent survey of interviewees showed that despite prior education, many find it challenging to retain and recall the specifics of machine learning algorithms. For instance, a significant number of those who studied these topics in graduate school report difficulties when revisiting the material after a period of time. The data indicates that current preparation methods, such as reviewing textbooks like ISLR and note-taking, are not as effective as desired for a large portion of candidates. These statistics highlight the need for more effective strategies and resources to help reinforce machine learning concepts for interview success.
Mimansa Jaiswal
@MimansaJ
·
Feb 24 I interviewed for LLM/ML research scientist/engineering positions last Fall. Over 200 applications, 100 interviews, many rejections & some offers later, I decided to write the process down, along with the resources I used.Links to the process & resources in the following tweets
Francisco Moretti
@franmoretti_
·
Apr 17 AI mock interview built in just 6 hours using ElevenLabsHelping my GF practice for her first role.Features
Any interview topic and difficulty level
Instant feedback on your answers
Personalized suggestions to improve your answers
Final score and a detailed report
sankalp
@dejavucoder
·
Feb 15 my brother in law is a machine learning engineer @ amazon. he usually asks LLM related questions to interview candidates but after watching aella’s latest podcast, he has started asking “what is correlation” and to his surprise, 90% fail. they don’t know how to define it.
Enes Poyraz
@ens_pyrz
·
Apr 18 Solving technical interview Questions is like asking mathematician to calculate 32423 x 23124 in their head. We have calculators for that. And now we have LLMs for interview Questions. The process is just dumb.
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