More reading: Receiver operating characteristic (Wikipedia). Some Common Facebook Interview Questions. For instance, Amazon is using recommendation system to provide goods that customers might also like. The 819 most common interview questions asked at Facebook, Google and more. Many algorithms can be expressed in terms of inner products. Q25: What’s the “kernel trick” and how is it useful? More reading: What are the typical use cases for different machine learning algorithms? whenever the "fast" one breaks, we use the other one to test the floor right beneath it. Answer: Don’t think that this is a trick question! Make sure you have a choice and make sure you can explain different algorithms so simply and effectively that a five-year-old could grasp the basics! Q41: What are the last machine learning papers you’ve read? Q28: Pick an algorithm. (Quora), What is the difference between “likelihood” and “probability”? Pre-IPO, they asked me to write a paper on the valuation of Facebook. More reading: What are some of the best research papers/books for machine learning? To accomplish that, you’ll have to answer some tricky Facebook interview questions to prove your caliber. You are given 2 identical eggs. More reading: Where to get free GPU cloud hours for machine learning. Q21: Name an example where ensemble techniques might be useful. A Russian gangster kidnaps you. What is Bayes’ Theorem? The bias-variance decomposition essentially decomposes the learning error from any algorithm by adding the bias, the variance and a bit of irreducible error due to noise in the underlying dataset. The Nature paper above describes how this was accomplished with “Monte-Carlo tree search with deep neural networks that have been trained by supervised learning, from human expert games, and by reinforcement learning from games of self-play.”, More reading: Mastering the game of Go with deep neural networks and tree search (Nature). As mentioned previously, Facebook will ask you questions that fall into certain categories like behavioral, design, strategy, estimation, and metric questions. More reading: What is the difference between a primary and foreign key in SQL? 29 Facebook Machine Learning Engineer interview questions and 28 interview reviews. Soon realize that even a 1 story drop is too much for a freaking egg. Concurrency. (Stack Overflow). Spark is the big data tool most in demand now, able to handle immense datasets with speed. Say you had a 60% chance of actually having the flu after a flu test, but out of people who had the flu, the test will be false 50% of the time, and the overall population only has a 5% chance of having the flu. Recommendation systemhas been a hot topic for a long time. Q18: What’s the F1 score? You want to find the floor at which the bulbs will break when dropped. In order to help resolve that, we have curated a list of 51 key questions that you might encounter in a machine learning interview. Create an account or log into Facebook. Following are the most frequently asked questions along with a few pointers to the things that interviewers want you to consider while designing the system. Each house has some amount of cash. More reading: Glassdoor machine learning interview questions. Share photos and videos, send messages and get updates. 10 Minutes to Building A Machine Learning Pipeline With Apache Airflow, Three Recommendations For Making The Most Of Valuable Data. Springboard has created a free guide to data science interviews, where we learned exactly how these interviews are designed to trip up candidates! Somebody who is truly passionate about machine learning will have gone off and done side projects on their own, and have a good idea of what great datasets are out there. Approaching each question with a predefined method will enable you to build strong interview habits. Answer: Supervised learning requires training labeled data. What is deep learning, and how does it contrast with other machine learning algorithms? (Stack Overflow), Using k-fold cross-validation for time-series model selection (CrossValidated), 8 Tactics to Combat Imbalanced Classes in Your Machine Learning Dataset (Machine Learning Mastery), Regression vs Classification (Math StackExchange), How to Evaluate Machine Learning Algorithms (Machine Learning Mastery), Evaluating a logistic regression (CrossValidated), 50 Top Open Source Tools for Big Data (Datamation), Writing pseudocode for parallel programming (Stack Overflow), Array versus linked list (Stack Overflow), 31 Free Data Visualization Tools (Springboard), How to Implement A Recommendation System? Understanding the context of your pending interview—i.e. 3.3 Learn a consistent method for answering PM interview questions. Database. Machine learning interview questions often look towards the details. More reading: Type I and type II errors (Wikipedia). Answer: The Netflix Prize was a famed competition where Netflix offered $1,000,000 for a better collaborative filtering algorithm. The probability of raining in Seattle is 50%. . More reading: Three Recommendations For Making The Most Of Valuable Data. I'm sorry–could you repeat that qustion, please? Answer: Bias is error due to erroneous or overly simplistic assumptions in the learning algorithm you’re using. Make sure that you’re totally comfortable with the language of your choice to express that logic. Bayes’ Theorem is the basis behind a branch of machine learning that most notably includes the Naive Bayes classifier. But if he spin the revolver then the counter will be reset and now there are 4 empty slots and 2 have bullets in them.

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