Watch This To Not Fail Your Next ML Interview

Summary

In this insightful video, the speaker shares their experience from a machine learning internship interview at Amazon, discussing the types of questions asked and providing valuable tips for preparation. They cover behavioral questions linked to Amazon's leadership principles, technical machine learning queries, and emphasize the importance of reviewing fundamental concepts. The speaker also regrets not knowing the interview team's focus and advises asking the recruiter for more information, preparing stories for behavioral questions in the STAR format, and having questions ready for the interviewers.

Takeaways

• 🔎 The speaker is preparing for a machine learning internship interview at Amazon and shares their experience to help others prepare.
• 🗣️ The interview consisted of an introduction, behavioral questions, and technical questions related to machine learning and data science.
• ⏳ The interview lasted about one hour, with different sections allotted specific time frames for various types of questions.
• 💡 Behavioral questions aimed to assess the candidate's fit with Amazon's 16 leadership principles, which are crucial for the company's hiring process.
• 📝 The speaker recommends preparing 2-4 stories for behavioral questions in the STAR format (Situation, Task, Action, Result) to demonstrate leadership skills and domain expertise.
• 🧠 Technical questions tested the candidate's breadth of knowledge in machine learning, starting with simple questions and gradually becoming more complex.
• 📚 The speaker emphasizes the importance of reviewing notes from machine learning courses to recall fundamental concepts for the interview.
• 🤔 The speaker regrets not knowing the team's focus beforehand and advises candidates to inquire about the team's domain expertise when applying.
• 📉 The speaker admits to making simple mistakes during the interview and suggests reviewing known material to avoid such errors.
• 🤷‍♂️ When unsure of an answer, it's better to admit not knowing rather than attempting to fabricate a response on the spot.
• 📈 The speaker provides tips for the 'tell me about yourself' section and suggests preparing questions for the interviewers to leave a good impression.
• 👍 The video aims to be a valuable resource for those preparing for similar interviews, with the hope that it will help them succeed.

Q & A

What is the main focus of the video transcript?

The main focus of the video transcript is to share the experience of a machine learning internship interview at Amazon, including the types of questions asked and tips for better preparation.

How long did the interview last according to the transcript?

The interview lasted about one hour.

What types of questions were asked during the interview?

The interview included self-introduction, behavioral questions, and technical questions related to machine learning and data science.

What is Amazon's approach to defining their values?

Amazon has 16 leadership principles which they live and hire by, which were used to assess the candidate's fit for the company.

Can you provide an example of a behavioral question asked during the interview?

One of the examples given is 'Tell me about a time where you had to remove a roadblock so that your team could progress in the project.'

What is PCA and why was it mentioned in the interview?

PCA stands for Principal Component Analysis, a statistical technique used for dimensionality reduction. It was mentioned to assess the candidate's knowledge in machine learning.

What is the significance of the F1 score, precision, and recall in the context of the interview?

The F1 score, precision, and recall are metrics used in machine learning to evaluate the performance of classification models. They were mentioned as part of the technical questions.

What is the STAR format mentioned in the transcript and why is it important for behavioral questions?

The STAR format stands for Situation, Task, Action, and Result. It is important for structuring responses to behavioral questions to clearly demonstrate leadership skills and experiences.

What regrets did the interviewee express about their interview preparation?

The interviewee regretted not knowing the specific team they were interviewing with, not having more stories prepared for behavioral questions, and making unnecessary errors during the interview.

What tips does the interviewee provide for future interviewees?

The interviewee suggests preparing stories in the STAR format, reviewing notes from machine learning courses, knowing fundamentals well, and being honest about not knowing an answer if it comes up during the interview.

What was the interviewee's strategy for asking questions at the end of the interview?

The interviewee advises preparing three questions to ask the interviewers, as not asking any questions can leave a negative impression.