Full Data Science Mock Interview! (featuring Kylie Ying)

Check out Mobile Pixels! https://bit.ly/3WKUC55 In this video we walk through a full-length data science interview. The task in the video is to develop a model to identify bots on a social media platform. In the video we cover topics including feature vectorization, one-hot encodings, dataset building, and more! Check out Kylie's channel: @KylieYYing ------------------------- Follow me on social media! Instagram | https://www.instagram.com/keithgalli/ Twitter | https://twitter.com/keithgalli TikTok | https://tiktok.com/@keithgalli ------------------------- Practice your Python Pandas data science skills with problems on StrataScratch! https://stratascratch.com/?via=keith Join the Python Army to get access to perks! YouTube - https://www.youtube.com/channel/UCq6XkhO5SZ66N04IcPbqNcw/join Patreon - https://www.patreon.com/keithgalli *I use affiliate links on the products that I recommend. I may earn a purchase commission or a referral bonus from the usage of these links. ------------------------- Video timeline! 0:00 - Video overview & format 3:38 - Introductory Behavioral questions | Data science interview 9:11 - Social media platform bot issue task overview | Data science interview 16:51 - What are some features we should investigate regarding the bot issue? | Data science interview 26:27 - Classification model implementation details (using feature vectors) | Data science interview 43:03 - What would a dataset to train models to detect bots look like? How would you approach collecting this data? | Data science interview 53:03 - Technical implementation details (python libraries, cloud services, etc) | Data science interview 57:26 - Any questions for me? | Data science interview 1:05:07 - Post-interview breakdown & analysis Thank you to mobile pixels for sponsoring this video!