Как быстро освежить математику перед собесом

Pre-register for Stream 5 of the "ML Foundation" course: https://forms.yandex.ru/u/6a16ef41505... Follow MLinside on Telegram: https://t.me/+xPCRRLylQh5lMmI6 Does it seem like you need to relearn all the math for an ML interview? In practice, this isn't true. Most math interview questions aren't about complex proofs and formula derivations, but rather about understanding how models, metrics, and experiments work. In this video, Alexander Dubeykovsky (ML Engineer at Avito, former Yandex, MLinside expert) will discuss the most common math topics in ML interviews, how to quickly refresh your knowledge before the interview, and why problem-solving works much better than last-minute textbook reading. Who will find this video useful: ▪️Those preparing for ML interviews ▪️Junior and Middle-level ML engineers ▪️Data Scientists ▪️Students looking for their first job in ML ▪️Anyone who hasn't explored mathematics in a while and wants to quickly refresh their knowledge Subscribe to the MLinside channel and join our Telegram channel – there you can ask questions and discuss the course with other students: https://t.me/+xPCRRLylQh5lMmI6 In less than a month, our ML System Design course with Valery Babushkin starts. Sign up now while there are still spots available! Website with the course program and pricing: https://mlinside.ru/system-design/?ut... Pre-registration form: https://forms.yandex.ru/u/6a0436bd902... Timecodes: 0:00 – Introduction 0:51 – How math is asked in interviews 1:43 – Example from an interview at Avito 4:01 – One of the biggest mistakes when preparing for an interview 4:52 – Interview preparation advice 6:29 – About math topics 6:42 – First topic 7:27 – Second topic 7:46 – Third topic 8:33 – Fourth topic 9:47 – Fifth topic 10:15 – A word from Victor Cantora 11:43 – Bonus from Alexander 13:47 – Conclusion #machinelearning #ml #datascience #ai #python #mlinside #training #data_science #artificialintelligence #mlengineer