Netflix ML Question - Design a System to Predict Netflix Watch Times (Full mock interview)
Ace your machine learning interviews with Exponent’s ML engineer interview course: https://bit.ly/488VWnC This interview delves into the use of machine learning in predicting Netflix watch time. Our guest covers a wide range of topics, including data utilization, feature engineering, supervised and unsupervised approaches, and similarity metrics. They also discuss the potential for combining these approaches to create a versatile recommendation system. Additionally, the interview explores challenges related to model deployment, temporal effects, and considerations for retraining. This conversation shows the complexities of machine learning for watch time prediction. Chapters (Powered by ChapterMe) - 00:00 - Intro 00:29 - Design goal Netflix watch time prediction 01:36 - Access to user data demographic, movie, show features 04:47 - Training model for watch time prediction 09:42 - Sparse matrix, similarity search, metrics 13:12 - Pearson correlation for watch time prediction 15:02 - Unsupervised methods offer advantages over supervised 18:24 - Linear model embeddings simplify learning 19:03 - Deployment issues and model integration 23:16 - Matrices for similarity over latent factor models 24:17 - Issues with supervised hot feature vectors 25:22 - Supervised feature-based prediction using embedding space 27:43 - Outro Want more machine learning content? Fake News Detection System - Machine Learning Mock Interview - • Fake News Detection System - Machine Learn... Amazon Machine Learning Engineer Interview: K-Means Clustering - • Amazon Machine Learning Engineer Interview... How to Become a Machine Learning Engineer - • How to Become a Machine Learning Engineer 👉 Subscribe to our channel: http://bit.ly/exponentyt 🕊️ Follow us on Twitter: http://bit.ly/exptweet 💙 Like us on Facebook for special discounts: http://bit.ly/exponentfb 📷 Check us out on Instagram: http://bit.ly/exponentig 📹 Watch us on TikTok: https://bit.ly/exponenttiktok ABOUT US: Did you enjoy this video? Want to land your dream career? Exponent is an online community, course, and coaching platform to help you ace your upcoming interview. Exponent has helped people land their dream careers at companies like Google, Microsoft, Amazon, and high-growth startups. Exponent is currently licensed by Stanford, Yale, UW, and others. Our courses include interview lessons, questions, and complete answers with video walkthroughs. Access hours of real interview videos, where we analyze what went right or wrong, and our 1000+ community of expert coaches and industry professionals, to help you get your dream job and more! #techjobinterviewprep #interviewtips #jobinterviewpreparation #Exponent #machinelearningengineer #MachineLearning #NetflixPredictions #InterviewPreparation #NetflixWatchTimePrediction #recommendationsystems

Spotify ML Question - Design a Recommendation System (Full mock interview)

Amazon Data Engineer Streaming and Analytics Interview

Brexit: The Disaster Britain Still Can’t Escape

ML System Design Mock Interview - Build an ML System That Classifies Which Tweets Are Toxic

Dave : Notion

Full ML Design Mock by ex-Meta Staff Engineer (with feedback)

Harmful Content Detection / Content Moderation | ML System Design Problem Breakdown

Google system design interview: Design Spotify (with ex-Google EM)

Top 6 ML Engineer Interview Questions (with Snapchat MLE)

Google Systems Design Interview With An Ex-Googler

Machine Learning Question - Training AI to Detect Bots (Full mock interview)

Instagram ML Question - Design a Ranking Model (Full Mock Interview with Senior Meta ML Engineer)

God Says:"I JUST CONFIRMED — ONLY YOU CAN SEE THIS LETTER"/God Message Now/God Message

A Jane Street Trading Mock Interview with Graham and Andrea

Amazon System Design Interview: Design Parking Garage

Deep Dive into LLMs like ChatGPT

Machine Learning for Everybody – Full Course

ML Foundations for AI Engineers (in 34 Minutes)

How I Prepared for ML System Design Interviews at Meta
![Yann LeCun's $1B Bet Against LLMs [Part 1]](https://i.ytimg.com/vi/kYkIdXwW2AE/hq720.jpg?sqp=-oaymwEbCNAFEJQDSFryq4qpAw0IARUAAIhCGAG4AvcY&rs=AOn4CLBvMdKvkZHL9Earmgc5OX3Iuc1UUQ&usqp=CCc)
