timecodes ----------------- 1:06 - intro 1:21 - What the video will be about 2:26 - "Few words" about the speaker 4:49 - Short AirBnB business story 6:58 - How did AirBnB grow after long unpopularity period: user surveys 10:05 - Data science is about considering all users 14:20 - Case 1. Marginal-return (where to invest to get the most of money?) 18:52 - Case 2. Experiments 23:35 - Legal hosting. Recognizing twins listings 26:46 - Building tools. Bycycle-condo metaphor 29:18 - Tools in AirBnB 33:02 - Knowledge repo 36:00 - Superset (about dashboards and nice visual, open-source tableua:) ) 38:00 - Questions
Incredibly insightful for someone looking to go into data science! It's great to hear some specifics of the job from an actual data scientist at Airbnb.
The accent is just delecious!) An the talk is interesting. But would have been better if someone had given the microphones to people who ask quastions. Or at least if Martin had repeated the questions, because personally I didn't hear what questions were about
Your tools are making me cry relative to my current job. I really like the internal libraries, common data processing utilities and blog post with peer review oh damn. And this was 4 years ago wtf
timecodes
-----------------
1:06 - intro
1:21 - What the video will be about
2:26 - "Few words" about the speaker
4:49 - Short AirBnB business story
6:58 - How did AirBnB grow after long unpopularity period: user surveys
10:05 - Data science is about considering all users
14:20 - Case 1. Marginal-return (where to invest to get the most of money?)
18:52 - Case 2. Experiments
23:35 - Legal hosting. Recognizing twins listings
26:46 - Building tools. Bycycle-condo metaphor
29:18 - Tools in AirBnB
33:02 - Knowledge repo
36:00 - Superset (about dashboards and nice visual, open-source tableua:) )
38:00 - Questions
Incredibly insightful for someone looking to go into data science! It's great to hear some specifics of the job from an actual data scientist at Airbnb.
The accent is just delecious!) An the talk is interesting.
But would have been better if someone had given the microphones to people who ask quastions. Or at least if Martin had repeated the questions, because personally I didn't hear what questions were about
Your tools are making me cry relative to my current job. I really like the internal libraries, common data processing utilities and blog post with peer review oh damn. And this was 4 years ago wtf
very insightful ..